A B C D E F G H I K L M N O P Q R S T U V W X Z
All Classes All Packages
All Classes All Packages
All Classes All Packages
A
- a - Variable in class org.apache.commons.statistics.distribution.TrapezoidalDistribution
-
Lower limit of this distribution (inclusive).
- a - Variable in class org.apache.commons.statistics.distribution.TriangularDistribution
-
Lower limit of this distribution (inclusive).
- ab - Variable in class org.apache.commons.statistics.descriptive.UInt128
-
bits 128-65.
- ab - Variable in class org.apache.commons.statistics.descriptive.UInt192
-
bits 192-129 (high 64-bits).
- ab - Variable in class org.apache.commons.statistics.descriptive.UInt96
-
bits 96-33.
- absoluteThreshold - Variable in class org.apache.commons.statistics.inference.BrentOptimizer
-
Absolute threshold.
- AbstractContinuousDistribution - Class in org.apache.commons.statistics.distribution
-
Base class for probability distributions on the reals.
- AbstractContinuousDistribution() - Constructor for class org.apache.commons.statistics.distribution.AbstractContinuousDistribution
- AbstractDiscreteDistribution - Class in org.apache.commons.statistics.distribution
-
Base class for integer-valued discrete distributions.
- AbstractDiscreteDistribution() - Constructor for class org.apache.commons.statistics.distribution.AbstractDiscreteDistribution
- accept(double) - Method in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
Updates the state of the statistics to reflect the addition of
value
. - accept(double) - Method in class org.apache.commons.statistics.descriptive.FirstMoment
-
Updates the state of the statistic to reflect the addition of
value
. - accept(double) - Method in class org.apache.commons.statistics.descriptive.GeometricMean
-
Updates the state of the statistic to reflect the addition of
value
. - accept(double) - Method in class org.apache.commons.statistics.descriptive.Kurtosis
-
Updates the state of the statistic to reflect the addition of
value
. - accept(double) - Method in class org.apache.commons.statistics.descriptive.Max
-
Updates the state of the statistic to reflect the addition of
value
. - accept(double) - Method in class org.apache.commons.statistics.descriptive.Mean
-
Updates the state of the statistic to reflect the addition of
value
. - accept(double) - Method in class org.apache.commons.statistics.descriptive.Min
-
Updates the state of the statistic to reflect the addition of
value
. - accept(double) - Method in class org.apache.commons.statistics.descriptive.Product
-
Updates the state of the statistic to reflect the addition of
value
. - accept(double) - Method in class org.apache.commons.statistics.descriptive.Skewness
-
Updates the state of the statistic to reflect the addition of
value
. - accept(double) - Method in class org.apache.commons.statistics.descriptive.StandardDeviation
-
Updates the state of the statistic to reflect the addition of
value
. - accept(double) - Method in class org.apache.commons.statistics.descriptive.Sum
-
Updates the state of the statistic to reflect the addition of
value
. - accept(double) - Method in class org.apache.commons.statistics.descriptive.SumOfCubedDeviations
-
Updates the state of the statistic to reflect the addition of
value
. - accept(double) - Method in class org.apache.commons.statistics.descriptive.SumOfFourthDeviations
-
Updates the state of the statistic to reflect the addition of
value
. - accept(double) - Method in class org.apache.commons.statistics.descriptive.SumOfLogs
-
Updates the state of the statistic to reflect the addition of
value
. - accept(double) - Method in class org.apache.commons.statistics.descriptive.SumOfSquaredDeviations
-
Updates the state of the statistic to reflect the addition of
value
. - accept(double) - Method in class org.apache.commons.statistics.descriptive.SumOfSquares
-
Updates the state of the statistic to reflect the addition of
value
. - accept(double) - Method in class org.apache.commons.statistics.descriptive.Variance
-
Updates the state of the statistic to reflect the addition of
value
. - accept(int) - Method in class org.apache.commons.statistics.descriptive.IntMax
-
Updates the state of the statistic to reflect the addition of
value
. - accept(int) - Method in class org.apache.commons.statistics.descriptive.IntMean
-
Updates the state of the statistic to reflect the addition of
value
. - accept(int) - Method in class org.apache.commons.statistics.descriptive.IntMin
-
Updates the state of the statistic to reflect the addition of
value
. - accept(int) - Method in class org.apache.commons.statistics.descriptive.IntStandardDeviation
-
Updates the state of the statistic to reflect the addition of
value
. - accept(int) - Method in class org.apache.commons.statistics.descriptive.IntStatistics
-
Updates the state of the statistics to reflect the addition of
value
. - accept(int) - Method in class org.apache.commons.statistics.descriptive.IntSum
-
Updates the state of the statistic to reflect the addition of
value
. - accept(int) - Method in class org.apache.commons.statistics.descriptive.IntSumOfSquares
-
Updates the state of the statistic to reflect the addition of
value
. - accept(int) - Method in class org.apache.commons.statistics.descriptive.IntVariance
-
Updates the state of the statistic to reflect the addition of
value
. - accept(long) - Method in class org.apache.commons.statistics.descriptive.LongMax
-
Updates the state of the statistic to reflect the addition of
value
. - accept(long) - Method in class org.apache.commons.statistics.descriptive.LongMean
-
Updates the state of the statistic to reflect the addition of
value
. - accept(long) - Method in class org.apache.commons.statistics.descriptive.LongMin
-
Updates the state of the statistic to reflect the addition of
value
. - accept(long) - Method in class org.apache.commons.statistics.descriptive.LongStandardDeviation
-
Updates the state of the statistic to reflect the addition of
value
. - accept(long) - Method in class org.apache.commons.statistics.descriptive.LongStatistics
-
Updates the state of the statistics to reflect the addition of
value
. - accept(long) - Method in class org.apache.commons.statistics.descriptive.LongSum
-
Updates the state of the statistic to reflect the addition of
value
. - accept(long) - Method in class org.apache.commons.statistics.descriptive.LongSumOfSquares
-
Updates the state of the statistic to reflect the addition of
value
. - accept(long) - Method in class org.apache.commons.statistics.descriptive.LongVariance
-
Updates the state of the statistic to reflect the addition of
value
. - ACTION_ERROR - Static variable in class org.apache.commons.statistics.ranking.NaturalRanking
-
Raise an exception for values.
- ACTION_NEG_INF - Static variable in class org.apache.commons.statistics.ranking.NaturalRanking
-
Map values to negative infinity.
- ACTION_POS_INF - Static variable in class org.apache.commons.statistics.ranking.NaturalRanking
-
Map values to positive infinity.
- add(double, double) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest.Candidates
-
Adds the (key, value) pair.
- add(int) - Method in class org.apache.commons.statistics.ranking.NaturalRanking.IntList
-
Adds the value to the list.
- add(int, int) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest.XYList
-
Adds the value to the list.
- add(long) - Method in class org.apache.commons.statistics.descriptive.Int128
-
Adds the value.
- add(DD, long) - Static method in class org.apache.commons.statistics.inference.StatisticUtils
-
Adds the value to the sum.
- add(Int128) - Method in class org.apache.commons.statistics.descriptive.Int128
-
Adds the value.
- add(Statistic) - Method in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
-
Add the statistic to the statistics to compute.
- add(Statistic) - Method in class org.apache.commons.statistics.descriptive.IntStatistics.Builder
-
Add the statistic to the statistics to compute.
- add(Statistic) - Method in class org.apache.commons.statistics.descriptive.LongStatistics.Builder
-
Add the statistic to the statistics to compute.
- add(UInt128) - Method in class org.apache.commons.statistics.descriptive.UInt128
-
Adds the value in-place.
- add(UInt192) - Method in class org.apache.commons.statistics.descriptive.UInt192
-
Adds the value.
- add(UInt96) - Method in class org.apache.commons.statistics.descriptive.UInt96
-
Adds the value.
- add(T, double[]) - Static method in class org.apache.commons.statistics.descriptive.Statistics
-
Add all the
values
to thestatistic
. - add(T, int[]) - Static method in class org.apache.commons.statistics.descriptive.Statistics
-
Add all the
values
to thestatistic
. - add(T, long[]) - Static method in class org.apache.commons.statistics.descriptive.Statistics
-
Add all the
values
to thestatistic
. - addCandidate(UnconditionedExactTest.Candidates, double, double, double, double) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Add point 2 to the list of minima if neither neighbour value is lower.
- addPair(double, double) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest.Candidates
-
Add the (key, value) pair to the data.
- addPositive(long) - Method in class org.apache.commons.statistics.descriptive.UInt128
-
Adds the value in place.
- addPositive(long) - Method in class org.apache.commons.statistics.descriptive.UInt96
-
Adds the value.
- addSquare(long) - Method in class org.apache.commons.statistics.descriptive.UInt192
-
Adds the squared value
x * x
. - allMatch(double, double[]) - Static method in class org.apache.commons.statistics.inference.OneWayAnova
-
Return true if all values in the array match the specified value.
- allMatch(Collection<double[]>) - Static method in class org.apache.commons.statistics.inference.OneWayAnova
-
Return true if all values in the arrays match.
- alpha - Variable in class org.apache.commons.statistics.distribution.BetaDistribution
-
First shape parameter.
- alternative - Variable in class org.apache.commons.statistics.inference.BinomialTest
-
Alternative hypothesis.
- alternative - Variable in class org.apache.commons.statistics.inference.FisherExactTest
-
Alternative hypothesis.
- alternative - Variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Alternative hypothesis.
- alternative - Variable in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
Alternative hypothesis.
- alternative - Variable in class org.apache.commons.statistics.inference.TTest
-
Alternative hypothesis.
- alternative - Variable in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Alternative hypothesis.
- alternative - Variable in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Alternative hypothesis.
- AlternativeHypothesis - Enum in org.apache.commons.statistics.inference
-
Represents an alternative hypothesis for a hypothesis test.
- AlternativeHypothesis() - Constructor for enum org.apache.commons.statistics.inference.AlternativeHypothesis
- aov(Collection<double[]>, double[]) - Static method in class org.apache.commons.statistics.inference.OneWayAnova
-
Performs an ANOVA test for a collection of category data, evaluating the null hypothesis that there is no difference among the means of the data categories.
- apply(double[]) - Method in class org.apache.commons.statistics.ranking.NaturalRanking
-
Rank
data
using the natural ordering on floating-point values, with NaN values handled according tonanStrategy
and ties resolved usingtiesStrategy
. - apply(double[]) - Method in interface org.apache.commons.statistics.ranking.RankingAlgorithm
-
Performs a rank transformation on the input data, returning an array of ranks.
- apply(double[], int[]) - Method in interface org.apache.commons.statistics.descriptive.NaNTransformer
-
Pre-process the data for partitioning.
- apply(double[], int[]) - Method in class org.apache.commons.statistics.descriptive.NaNTransformers.ErrorNaNTransformer
- apply(double[], int[]) - Method in class org.apache.commons.statistics.descriptive.NaNTransformers.ExcludeNaNTransformer
- apply(double[], int[]) - Method in class org.apache.commons.statistics.descriptive.NaNTransformers.IncludeNaNTransformer
- Arguments - Class in org.apache.commons.statistics.inference
-
Argument validation methods.
- Arguments() - Constructor for class org.apache.commons.statistics.inference.Arguments
-
No instances.
- ArgumentUtils - Class in org.apache.commons.statistics.distribution
-
Utilities for argument validation.
- ArgumentUtils() - Constructor for class org.apache.commons.statistics.distribution.ArgumentUtils
-
No instances.
- ArrayRealSquareMatrix(int, double[], int) - Constructor for class org.apache.commons.statistics.inference.SquareMatrixSupport.ArrayRealSquareMatrix
- ASYMPTOTIC - org.apache.commons.statistics.inference.PValueMethod
-
Use the asymptotic distribution of the test statistic to evaluate the p-value.
- AUTO - org.apache.commons.statistics.inference.PValueMethod
-
Automatically choose the method to evaluate the p-value.
- AUTO_LIMIT - Static variable in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
Limit on sample size for the exact p-value computation for the auto mode.
- AUTO_LIMIT - Static variable in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Limit on sample size for the exact p-value computation for the auto mode.
- AVERAGE - org.apache.commons.statistics.ranking.TiesStrategy
-
Tied values are assigned the average of the applicable ranks.
B
- b - Variable in class org.apache.commons.statistics.distribution.TrapezoidalDistribution
-
Start of the trapezoid constant density.
- b - Variable in class org.apache.commons.statistics.distribution.TriangularDistribution
-
Upper limit of this distribution (inclusive).
- BaseSignificanceResult - Class in org.apache.commons.statistics.inference
-
Base implementation for the result of a test for significance.
- BaseSignificanceResult(double, double) - Constructor for class org.apache.commons.statistics.inference.BaseSignificanceResult
-
Create an instance.
- beta - Variable in class org.apache.commons.statistics.distribution.BetaDistribution
-
Second shape parameter.
- beta - Variable in class org.apache.commons.statistics.distribution.GumbelDistribution
-
Scale parameter.
- beta - Variable in class org.apache.commons.statistics.distribution.LaplaceDistribution
-
The scale parameter.
- BetaDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the beta distribution.
- BetaDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.BetaDistribution
- biased - Variable in class org.apache.commons.statistics.descriptive.IntStandardDeviation
-
Flag to control if the statistic is biased, or should use a bias correction.
- biased - Variable in class org.apache.commons.statistics.descriptive.IntVariance
-
Flag to control if the statistic is biased, or should use a bias correction.
- biased - Variable in class org.apache.commons.statistics.descriptive.Kurtosis
-
Flag to control if the statistic is biased, or should use a bias correction.
- biased - Variable in class org.apache.commons.statistics.descriptive.LongStandardDeviation
-
Flag to control if the statistic is biased, or should use a bias correction.
- biased - Variable in class org.apache.commons.statistics.descriptive.LongVariance
-
Flag to control if the statistic is biased, or should use a bias correction.
- biased - Variable in class org.apache.commons.statistics.descriptive.Skewness
-
Flag to control if the statistic is biased, or should use a bias correction.
- biased - Variable in class org.apache.commons.statistics.descriptive.StandardDeviation
-
Flag to control if the statistic is biased, or should use a bias correction.
- biased - Variable in class org.apache.commons.statistics.descriptive.StatisticsConfiguration
-
Flag to control if the statistic is biased, or should use a bias correction.
- biased - Variable in class org.apache.commons.statistics.descriptive.Variance
-
Flag to control if the statistic is biased, or should use a bias correction.
- BIG - Static variable in class org.apache.commons.statistics.distribution.ExtendedPrecision
-
Threshold for a big number that may overflow when squared.
- BigIntegerStatisticResult - Interface in org.apache.commons.statistics.descriptive
-
Represents the
BigInteger
result of a statistic computed over a set of values. - BINARY_SEARCH - Static variable in class org.apache.commons.statistics.inference.Searches
-
Range threshold to use a binary search.
- binom(int, int) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Compute the binomial coefficient binom(n, k).
- BinomialDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the binomial distribution.
- BinomialDistribution(int, double) - Constructor for class org.apache.commons.statistics.distribution.BinomialDistribution
- BinomialTest - Class in org.apache.commons.statistics.inference
-
Implements binomial test statistics.
- BinomialTest(AlternativeHypothesis) - Constructor for class org.apache.commons.statistics.inference.BinomialTest
- bma - Variable in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.RegularTrapezoidalDistribution
-
Cached value (b - a).
- BOSCHLOO - org.apache.commons.statistics.inference.UnconditionedExactTest.Method
-
Uses the p-value from Fisher's exact test.
- bp - Variable in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
Binomial probability of success (sampleSize / populationSize).
- bq - Variable in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
Binomial probability of failure ((populationSize - sampleSize) / populationSize).
- BracketFinder - Class in org.apache.commons.statistics.inference
-
Provide an interval that brackets a local minimum of a function.
- BracketFinder() - Constructor for class org.apache.commons.statistics.inference.BracketFinder
-
Constructor with default values
100, 100000
(see theother constructor
). - BracketFinder(double, int) - Constructor for class org.apache.commons.statistics.inference.BracketFinder
-
Create a bracketing interval finder.
- BrentOptimizer - Class in org.apache.commons.statistics.inference
-
For a function defined on some interval
(lo, hi)
, this class finds an approximationx
to the point at which the function attains its minimum. - BrentOptimizer(double, double) - Constructor for class org.apache.commons.statistics.inference.BrentOptimizer
-
The arguments are used to implement the original stopping criterion of Brent's algorithm.
- BrentOptimizer.PointValuePair - Class in org.apache.commons.statistics.inference
-
This class holds a point and the value of an objective function at this point.
- build() - Method in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
-
Builds a
DoubleStatistics
instance. - build() - Method in class org.apache.commons.statistics.descriptive.IntStatistics.Builder
-
Builds a
IntStatistics
instance. - build() - Method in class org.apache.commons.statistics.descriptive.LongStatistics.Builder
-
Builds a
LongStatistics
instance. - build(double...) - Method in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
-
Builds a
DoubleStatistics
instance using the inputvalues
. - build(int...) - Method in class org.apache.commons.statistics.descriptive.IntStatistics.Builder
-
Builds a
IntStatistics
instance using the inputvalues
. - build(long...) - Method in class org.apache.commons.statistics.descriptive.LongStatistics.Builder
-
Builds a
LongStatistics
instance using the inputvalues
. - builder(Statistic...) - Static method in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
Returns a new builder configured to create instances to compute the specified
statistics
. - builder(Statistic...) - Static method in class org.apache.commons.statistics.descriptive.IntStatistics
-
Returns a new builder configured to create instances to compute the specified
statistics
. - builder(Statistic...) - Static method in class org.apache.commons.statistics.descriptive.LongStatistics
-
Returns a new builder configured to create instances to compute the specified
statistics
. - Builder() - Constructor for class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
-
Create an instance.
- Builder() - Constructor for class org.apache.commons.statistics.descriptive.IntStatistics.Builder
-
Create an instance.
- Builder() - Constructor for class org.apache.commons.statistics.descriptive.LongStatistics.Builder
-
Create an instance.
C
- c - Variable in class org.apache.commons.statistics.descriptive.UInt128
-
bits 64-33.
- c - Variable in class org.apache.commons.statistics.descriptive.UInt192
-
bits 128-97.
- c - Variable in class org.apache.commons.statistics.descriptive.UInt96
-
bits 32-1 (low 32-bits).
- c - Variable in class org.apache.commons.statistics.distribution.LevyDistribution
-
Scale parameter.
- c - Variable in class org.apache.commons.statistics.distribution.TrapezoidalDistribution
-
End of the trapezoid constant density.
- c - Variable in class org.apache.commons.statistics.distribution.TriangularDistribution
-
Mode of this distribution.
- cacheF - Static variable in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
A reference to a previously computed storage for f.
- calculateAbsoluteDifferences(double[]) - Static method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Calculates |z[i]| for all i.
- calculateAsymptoticPValue(double, int, double, double, AlternativeHypothesis, boolean) - Static method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Compute the asymptotic p-value using the Cureton normal approximation.
- calculateAsymptoticPValue(double, int, int, double) - Method in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
Calculate the asymptotic p-value using a Normal approximation.
- calculateDifferences(double, double[], double[]) - Static method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Calculates x[i] - mu - y[i] for all i.
- calculateExactPValue(double, int, int, AlternativeHypothesis) - Static method in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
Calculate the exact p-value.
- calculateExactPValue(int, int, AlternativeHypothesis) - Static method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Compute the exact p-value.
- calculateTieCorrection(double[]) - Static method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Calculate the tie correction.
- calculateW(double[], double[]) - Static method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Calculate the Wilcoxon positive-rank sum statistic.
- Candidates(int, double) - Constructor for class org.apache.commons.statistics.inference.UnconditionedExactTest.Candidates
-
Create an instance.
- CATEGORIES_REQUIRED - Static variable in exception org.apache.commons.statistics.inference.InferenceException
-
Error message for "categories
x < y
". - CauchyDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the Cauchy distribution.
- CauchyDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.CauchyDistribution
- cdf(double) - Static method in class org.apache.commons.statistics.distribution.CauchyDistribution
-
Compute the CDF of the Cauchy distribution with location 0 and scale 1.
- cdf(int) - Method in class org.apache.commons.statistics.inference.Hypergeom
-
Compute the cumulative distribution function (CDF) at the specified value.
- cdf(int, int, int) - Static method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Compute the cumulative density function of the Wilcoxon signed rank W+ statistic.
- cdf(int, int, int, int, double) - Static method in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
Compute the cumulative density function of the Mann-Whitney U1 statistic.
- cdfAlpha - Variable in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
Stored value of
parentNormal.cumulativeProbability(lower)
. - cdfB - Variable in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.RegularTrapezoidalDistribution
-
Cumulative probability at b.
- cdfC - Variable in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.RegularTrapezoidalDistribution
-
Cumulative probability at c.
- cdfDelta - Variable in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
Stored value of
parentNormal.probability(lower, upper)
. - cdfMode - Variable in class org.apache.commons.statistics.distribution.TriangularDistribution
-
Cumulative probability at the mode.
- checkArrayLength(double[]) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Verifies that
array
has length at least 2. - checkCategoriesRequiredSize(int, int) - Static method in class org.apache.commons.statistics.inference.Arguments
-
Check the categories size is the minimum required,
size >= required
. - checkCombineAssignable(FirstMoment, FirstMoment) - Static method in class org.apache.commons.statistics.descriptive.Statistics
-
Check left-hand side argument
a
isnull
or else the right-hand side argumentb
must be run-time assignable to the same class asa
so the statistics can be combined. - checkCombineCompatible(T, T) - Static method in class org.apache.commons.statistics.descriptive.Statistics
-
Check left-hand side argument
a
isnull
or else the right-hand side argumentb
must also be non-null
so the statistics can be combined. - checkExponent(int) - Static method in class org.apache.commons.statistics.inference.SquareMatrixSupport.ArrayRealSquareMatrix
-
Check the exponent is not negative.
- checkFinite(double) - Static method in class org.apache.commons.statistics.inference.Arguments
-
Check that the value is finite.
- checkNonNaN(double[]) - Static method in class org.apache.commons.statistics.inference.Arguments
-
Check that all values are not
Double.NaN
. - checkNonNegative(double) - Static method in class org.apache.commons.statistics.inference.Arguments
-
Check that the value is
>= 0
. - checkNonNegative(int) - Static method in class org.apache.commons.statistics.inference.Arguments
-
Check that the value is
>= 0
. - checkNonNegative(long[]) - Static method in class org.apache.commons.statistics.inference.Arguments
-
Check that all values are
>= 0
. - checkNonNegative(long[][]) - Static method in class org.apache.commons.statistics.inference.Arguments
-
Check that all values are
>= 0
. - checkNonZero(double, String, int) - Static method in class org.apache.commons.statistics.inference.ChiSquareTest
-
Check the array value is non-zero.
- checkNonZero(double, String, int) - Static method in class org.apache.commons.statistics.inference.GTest
-
Check the array value is non-zero.
- checkNumberOfProbabilities(int) - Static method in class org.apache.commons.statistics.descriptive.Quantile
-
Check the number of probabilities
n
is strictly positive. - checkOption(E, Set<E>) - Static method in class org.apache.commons.statistics.inference.Arguments
-
Check the option is allowed.
- checkProbabilities(double...) - Static method in class org.apache.commons.statistics.descriptive.Quantile
-
Check the probabilities
p
are in the range[0, 1]
. - checkProbability(double) - Static method in class org.apache.commons.statistics.descriptive.Quantile
-
Check the probability
p
is in the range[0, 1]
. - checkProbability(double) - Static method in class org.apache.commons.statistics.distribution.ArgumentUtils
-
Check the probability
p
is in the interval[0, 1]
. - checkRectangular(long[][]) - Static method in class org.apache.commons.statistics.inference.Arguments
-
Checks if the input array is rectangular.
- checkSamples(double[], double[]) - Static method in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
Ensures that the provided arrays fulfil the assumptions.
- checkSamples(double[], double[]) - Static method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Ensures that the provided arrays fulfil the assumptions.
- checkSampleSize(long) - Static method in class org.apache.commons.statistics.inference.TTest
-
Check sample data size.
- checkSignificance(double) - Static method in class org.apache.commons.statistics.inference.Arguments
-
Check the significance level is in the correct range.
- checkSize(int) - Static method in class org.apache.commons.statistics.descriptive.Quantile
-
Check the
size
is positive. - checkStrictlyPositive(double) - Static method in class org.apache.commons.statistics.inference.Arguments
-
Check that value is
> 0
. - checkStrictlyPositive(double[]) - Static method in class org.apache.commons.statistics.inference.Arguments
-
Check that all values are
> 0
. - checkStrictlyPositive(int) - Static method in class org.apache.commons.statistics.inference.Arguments
-
Check that value is
> 0
. - checkTable(int[][]) - Static method in class org.apache.commons.statistics.inference.Arguments
-
Check the input is a 2-by-2 contingency table.
- checkTable(int[][]) - Static method in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Check the input is a 2-by-2 contingency table.
- checkValuesRequiredSize(int, int) - Static method in class org.apache.commons.statistics.inference.Arguments
-
Check the values size is the minimum required,
size >= required
. - checkValuesSizeMatch(int, int) - Static method in class org.apache.commons.statistics.inference.Arguments
-
Check the values sizes are equal,
size1 == size2
. - ChiSquaredDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the chi-squared distribution.
- ChiSquaredDistribution(double) - Constructor for class org.apache.commons.statistics.distribution.ChiSquaredDistribution
- ChiSquareTest - Class in org.apache.commons.statistics.inference
-
Implements chi-square test statistics.
- ChiSquareTest(int) - Constructor for class org.apache.commons.statistics.inference.ChiSquareTest
- clear() - Method in class org.apache.commons.statistics.ranking.NaturalRanking.IntList
-
Clear the list.
- clip(double, double, double) - Static method in class org.apache.commons.statistics.distribution.LogUniformDistribution
-
Clip the value to the range [lower, upper].
- clip(double, double, double) - Static method in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
Clip the value to the range [lower, upper].
- clipProbability(double) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution
-
Clip the probability to the range [0, 1].
- clipToRange(double) - Method in class org.apache.commons.statistics.distribution.LogUniformDistribution
-
Clip the value to the range [lower, upper].
- clipToRange(double) - Method in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
Clip the value to the range [lower, upper].
- CLOSE_TO_ZERO - Static variable in class org.apache.commons.statistics.distribution.TDistribution.StudentsTDistribution
-
The threshold for the density function where the power function base minus 1 is close to zero.
- COLUMN - Static variable in class org.apache.commons.statistics.inference.ChiSquareTest
-
Name for the column.
- COLUMN_SUM - Static variable in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Error message text for zero column sums.
- combine(double, double, long, long) - Static method in class org.apache.commons.statistics.descriptive.FirstMoment
-
Combine the moments.
- combine(DoubleStatistics) - Method in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
Combines the state of the
other
statistics into this one. - combine(FirstMoment) - Method in class org.apache.commons.statistics.descriptive.FirstMoment
-
Combines the state of another
FirstMoment
into this one. - combine(GeometricMean) - Method in class org.apache.commons.statistics.descriptive.GeometricMean
- combine(IntMax) - Method in class org.apache.commons.statistics.descriptive.IntMax
- combine(IntMean) - Method in class org.apache.commons.statistics.descriptive.IntMean
- combine(IntMin) - Method in class org.apache.commons.statistics.descriptive.IntMin
- combine(IntStandardDeviation) - Method in class org.apache.commons.statistics.descriptive.IntStandardDeviation
- combine(IntStatistics) - Method in class org.apache.commons.statistics.descriptive.IntStatistics
-
Combines the state of the
other
statistics into this one. - combine(IntSum) - Method in class org.apache.commons.statistics.descriptive.IntSum
- combine(IntSumOfSquares) - Method in class org.apache.commons.statistics.descriptive.IntSumOfSquares
- combine(IntVariance) - Method in class org.apache.commons.statistics.descriptive.IntVariance
- combine(Kurtosis) - Method in class org.apache.commons.statistics.descriptive.Kurtosis
- combine(LongMax) - Method in class org.apache.commons.statistics.descriptive.LongMax
- combine(LongMean) - Method in class org.apache.commons.statistics.descriptive.LongMean
- combine(LongMin) - Method in class org.apache.commons.statistics.descriptive.LongMin
- combine(LongStandardDeviation) - Method in class org.apache.commons.statistics.descriptive.LongStandardDeviation
- combine(LongStatistics) - Method in class org.apache.commons.statistics.descriptive.LongStatistics
-
Combines the state of the
other
statistics into this one. - combine(LongSum) - Method in class org.apache.commons.statistics.descriptive.LongSum
- combine(LongSumOfSquares) - Method in class org.apache.commons.statistics.descriptive.LongSumOfSquares
- combine(LongVariance) - Method in class org.apache.commons.statistics.descriptive.LongVariance
- combine(Max) - Method in class org.apache.commons.statistics.descriptive.Max
- combine(Mean) - Method in class org.apache.commons.statistics.descriptive.Mean
- combine(Min) - Method in class org.apache.commons.statistics.descriptive.Min
- combine(Product) - Method in class org.apache.commons.statistics.descriptive.Product
- combine(Skewness) - Method in class org.apache.commons.statistics.descriptive.Skewness
- combine(StandardDeviation) - Method in class org.apache.commons.statistics.descriptive.StandardDeviation
- combine(Sum) - Method in class org.apache.commons.statistics.descriptive.Sum
- combine(SumOfCubedDeviations) - Method in class org.apache.commons.statistics.descriptive.SumOfCubedDeviations
-
Combines the state of another
SumOfCubedDeviations
into this one. - combine(SumOfFourthDeviations) - Method in class org.apache.commons.statistics.descriptive.SumOfFourthDeviations
-
Combines the state of another
SumOfFourthDeviations
into this one. - combine(SumOfLogs) - Method in class org.apache.commons.statistics.descriptive.SumOfLogs
- combine(SumOfSquaredDeviations) - Method in class org.apache.commons.statistics.descriptive.SumOfSquaredDeviations
-
Combines the state of another
SumOfSquaredDeviations
into this one. - combine(SumOfSquares) - Method in class org.apache.commons.statistics.descriptive.SumOfSquares
- combine(Variance) - Method in class org.apache.commons.statistics.descriptive.Variance
- combine(T) - Method in interface org.apache.commons.statistics.descriptive.StatisticAccumulator
-
Combines the state of the
other
statistic into this one. - combine(T, T) - Static method in class org.apache.commons.statistics.descriptive.Statistics
-
If the left-hand side argument
a
is non-null
, combine it with the right-hand side argumentb
. - combineMoment(FirstMoment, FirstMoment) - Static method in class org.apache.commons.statistics.descriptive.Statistics
-
If the left-hand side argument
a
is non-null
, combine it with the right-hand side argumentb
. - compareTo(NaturalRanking.DataPosition) - Method in class org.apache.commons.statistics.ranking.NaturalRanking.DataPosition
-
Compare this value to another.
- compose(DoubleConsumer...) - Static method in class org.apache.commons.statistics.descriptive.Statistics
-
Chain the
consumers
into a single composite consumer. - compose(IntConsumer...) - Static method in class org.apache.commons.statistics.descriptive.Statistics
-
Chain the
consumers
into a single composite consumer. - compose(LongConsumer...) - Static method in class org.apache.commons.statistics.descriptive.Statistics
-
Chain the
consumers
into a single composite consumer. - composeAsInt(DoubleConsumer...) - Static method in class org.apache.commons.statistics.descriptive.IntStatistics
-
Chain the
consumers
into a single compositeIntConsumer
. - composeAsLong(DoubleConsumer...) - Static method in class org.apache.commons.statistics.descriptive.LongStatistics
-
Chain the
consumers
into a single compositeLongConsumer
. - computeA(int, double, int[], int[]) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
Compute the factors floor(A-t) and ceil(A+t).
- computeAP(double[], double) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
Compute the power factors.
- computeCdf(int, int) - Static method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Compute the cumulative density function for the distribution of the Wilcoxon signed rank statistic.
- computeCdf(int, int, int, double) - Static method in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
Compute the cumulative density function of the Mann-Whitney U statistic.
- computeD(long, int, int, int) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Compute the D statistic from the integral D value.
- computeDegreesOfFreedom(int, int) - Static method in class org.apache.commons.statistics.inference.StatisticUtils
-
Compute the degrees of freedom as
n - 1 - m
. - computeDensity(double, boolean) - Method in class org.apache.commons.statistics.distribution.FDistribution
-
Compute the density at point x.
- computeDf(double, long, double, long) - Static method in class org.apache.commons.statistics.inference.TTest
-
Computes approximate degrees of freedom for two-sample t-test without the assumption of equal samples sizes or sub-population variances.
- computeGeometricMean(long, SumOfLogs) - Static method in class org.apache.commons.statistics.descriptive.GeometricMean
-
Compute the geometric mean.
- computeHomoscedasticT(double, double, double, long, double, double, long) - Static method in class org.apache.commons.statistics.inference.TTest
-
Computes t statistic for two-sample t-test under the hypothesis of equal sub-population variances.
- computeIndices(int, double[], double[]) - Method in class org.apache.commons.statistics.descriptive.Quantile
-
Compute the indices required for quantile interpolation.
- computeIntegralKolmogorovSmirnovStatistic(double[], double[], int[], long[]) - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Computes the two-sample Kolmogorov-Smirnov test statistic.
- computeInverseProbability(double, double, boolean) - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
Implementation for the inverse cumulative or survival probability.
- computeLogProbability(int) - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
Compute the log probability.
- computeMean() - Method in class org.apache.commons.statistics.descriptive.IntVariance
-
Compute the mean.
- computeMean() - Method in class org.apache.commons.statistics.descriptive.LongVariance
-
Compute the mean.
- computeMean(Int128, long) - Static method in class org.apache.commons.statistics.descriptive.IntMean
-
Compute the mean.
- computeMean(Int128, long) - Static method in class org.apache.commons.statistics.descriptive.LongMean
-
Compute the mean.
- computeNonFiniteValue(double[]) - Static method in class org.apache.commons.statistics.descriptive.FirstMoment
-
Compute the result in the event of non-finite values.
- computeP(double, double) - Static method in class org.apache.commons.statistics.inference.ChiSquareTest
-
Compute the chi-square test p-value.
- computeP(double, double) - Static method in class org.apache.commons.statistics.inference.GTest
-
Compute the G-test p-value.
- computeP(double, double) - Method in class org.apache.commons.statistics.inference.TTest
-
Computes p-value for the specified t statistic.
- computePValue(UnconditionedExactTest.XYList) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Compute the nuisance parameter and p-value for the binomial model given the list of possible tables.
- computeRatio(double[], long[]) - Static method in class org.apache.commons.statistics.inference.StatisticUtils
-
Gets the ratio between the sum of the observed and expected values.
- computeSqrt2aa(double) - Static method in class org.apache.commons.statistics.distribution.ExtendedPrecision
-
Compute
sqrt(2 * a * a)
. - computeSSDevN(UInt128, Int128, long) - Static method in class org.apache.commons.statistics.descriptive.IntVariance
-
Compute the sum-of-squared deviations multiplied by the count of values:
n * sum(x^2) - sum(x)^2
. - computeSSDevN(UInt192, Int128, long) - Static method in class org.apache.commons.statistics.descriptive.LongVariance
-
Compute the sum-of-squared deviations multiplied by the count of values:
n * sum(x^2) - sum(x)^2
. - computeStatistic(double[], double) - Static method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Computes the Wilcoxon signed ranked statistic comparing the differences between sample values
z = x - y
tomu
. - computeStatistic(double[], DoubleUnaryOperator, int[]) - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Computes the magnitude of the one-sample Kolmogorov-Smirnov test statistic.
- computeSumOfSquaredDeviations() - Method in class org.apache.commons.statistics.descriptive.IntVariance
-
Compute the sum of the squared deviations from the mean.
- computeSumOfSquaredDeviations() - Method in class org.apache.commons.statistics.descriptive.LongVariance
-
Compute the sum of the squared deviations from the mean.
- computeT(double, double, double, long, double, double, long) - Static method in class org.apache.commons.statistics.inference.TTest
-
Computes t statistic for two-sample t-test without the assumption of equal samples sizes or sub-population variances.
- computeT(double, double, long) - Static method in class org.apache.commons.statistics.inference.TTest
-
Computes t statistic for one-sample t-test.
- computeTest(double[], double) - Method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Performs a Wilcoxon signed ranked statistic comparing the differences between sample values
z = x - y
tomu
. - computeVariance(double) - Static method in class org.apache.commons.statistics.distribution.TDistribution.StudentsTDistribution
- computeVarianceOrStd(UInt128, Int128, long, boolean, boolean) - Static method in class org.apache.commons.statistics.descriptive.IntVariance
-
Compute the variance (or standard deviation).
- computeVarianceOrStd(UInt192, Int128, long, boolean, boolean) - Static method in class org.apache.commons.statistics.descriptive.LongVariance
-
Compute the variance (or standard deviation).
- computeXsqrt2pi(double) - Static method in class org.apache.commons.statistics.distribution.ExtendedPrecision
-
Compute
a * sqrt(2 * pi)
. - concatenateSamples(double, double[], double[]) - Static method in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
Concatenate the samples into one array.
- config - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
-
Configuration options for computation of statistics.
- config - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
Configuration options for computation of statistics.
- config - Variable in class org.apache.commons.statistics.descriptive.IntStatistics.Builder
-
Configuration options for computation of statistics.
- config - Variable in class org.apache.commons.statistics.descriptive.IntStatistics
-
Configuration options for computation of statistics.
- config - Variable in class org.apache.commons.statistics.descriptive.LongStatistics.Builder
-
Configuration options for computation of statistics.
- config - Variable in class org.apache.commons.statistics.descriptive.LongStatistics
-
Configuration options for computation of statistics.
- Constants - Class in org.apache.commons.statistics.distribution
-
Constants for distribution calculations.
- Constants() - Constructor for class org.apache.commons.statistics.distribution.Constants
-
No instances.
- consumer - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
The consumer of values.
- consumer - Variable in class org.apache.commons.statistics.descriptive.IntStatistics
-
The consumer of values.
- consumer - Variable in class org.apache.commons.statistics.descriptive.LongStatistics
-
The consumer of values.
- continuityCorrection - Variable in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
Perform continuity correction.
- continuityCorrection - Variable in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Perform continuity correction.
- ContinuityCorrection - Enum in org.apache.commons.statistics.inference
-
Represents an optional adjustment that is made when a discrete distribution is approximated by a continuous distribution.
- ContinuityCorrection() - Constructor for enum org.apache.commons.statistics.inference.ContinuityCorrection
- ContinuousDistribution - Interface in org.apache.commons.statistics.distribution
-
Interface for distributions on the reals.
- ContinuousDistribution.Sampler - Interface in org.apache.commons.statistics.distribution
-
Distribution sampling functionality.
- copy - Variable in class org.apache.commons.statistics.descriptive.Median
-
Flag to indicate if the data should be copied.
- copy - Variable in class org.apache.commons.statistics.descriptive.NaNTransformers.ErrorNaNTransformer
-
Set to
true
to use a copy of the data. - copy - Variable in class org.apache.commons.statistics.descriptive.NaNTransformers.ExcludeNaNTransformer
-
Set to
true
to use a copy of the data. - copy - Variable in class org.apache.commons.statistics.descriptive.NaNTransformers.IncludeNaNTransformer
-
Set to
true
to use a copy of the data. - copy - Variable in class org.apache.commons.statistics.descriptive.Quantile
-
Flag to indicate if the data should be copied.
- count - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
Count of values recorded.
- count - Variable in class org.apache.commons.statistics.descriptive.IntStatistics
-
Count of values recorded.
- count - Variable in class org.apache.commons.statistics.descriptive.LongStatistics
-
Count of values recorded.
- countZeros(double[]) - Static method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Count the number of zeros in the data.
- create() - Static method in class org.apache.commons.statistics.descriptive.GeometricMean
-
Creates an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.Int128
-
Create an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.IntMax
-
Creates an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.IntMean
-
Creates an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.IntMin
-
Creates an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.IntStandardDeviation
-
Creates an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.IntSum
-
Creates an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.IntSumOfSquares
-
Creates an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.IntVariance
-
Creates an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.Kurtosis
-
Creates an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.LongMax
-
Creates an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.LongMean
-
Creates an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.LongMin
-
Creates an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.LongStandardDeviation
-
Creates an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.LongSum
-
Creates an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.LongSumOfSquares
-
Creates an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.LongVariance
-
Creates an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.Max
-
Creates an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.Mean
-
Creates an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.Min
-
Creates an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.Product
-
Creates an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.Skewness
-
Creates an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.StandardDeviation
-
Creates an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.Sum
-
Creates an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.SumOfLogs
-
Creates an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.SumOfSquares
-
Creates an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.UInt128
-
Create an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.UInt192
-
Create an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.UInt96
-
Create an instance.
- create() - Static method in class org.apache.commons.statistics.descriptive.Variance
-
Creates an instance.
- create(double[]) - Static method in class org.apache.commons.statistics.descriptive.FirstMoment
-
Creates the first moment using a rolling algorithm.
- create(int, double[]) - Static method in class org.apache.commons.statistics.inference.SquareMatrixSupport
-
Creates a square matrix.
- create(BiFunction<R, S, T>, R, S) - Static method in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
-
Creates the object from the values
r
ands
. - create(Function<int[], T>, int[]) - Static method in class org.apache.commons.statistics.descriptive.IntStatistics.Builder
-
Creates the object from the
values
. - create(Function<long[], T>, long[]) - Static method in class org.apache.commons.statistics.descriptive.LongStatistics.Builder
-
Creates the object from the
values
. - create(Function<S, T>, S) - Static method in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
-
Creates the object from the
values
. - create(Sum, double[]) - Static method in class org.apache.commons.statistics.descriptive.FirstMoment
-
Creates the first moment.
- create(Sum, double[]) - Static method in class org.apache.commons.statistics.descriptive.SumOfCubedDeviations
-
Creates the sum of cubed deviations.
- create(Sum, double[]) - Static method in class org.apache.commons.statistics.descriptive.SumOfFourthDeviations
-
Creates the sum of fourth deviations.
- create(Sum, double[]) - Static method in class org.apache.commons.statistics.descriptive.SumOfSquaredDeviations
-
Creates the sum of squared deviations.
- create(FirstMoment, double[]) - Static method in class org.apache.commons.statistics.descriptive.SumOfSquaredDeviations
-
Creates the sum of squared deviations.
- create(SumOfCubedDeviations, double[]) - Static method in class org.apache.commons.statistics.descriptive.SumOfFourthDeviations
-
Creates the sum of fourth deviations.
- create(SumOfSquaredDeviations, double[]) - Static method in class org.apache.commons.statistics.descriptive.SumOfCubedDeviations
-
Creates the sum of cubed deviations.
- createBinomialModel(UnconditionedExactTest.XYList) - Static method in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Creates the binomial model p-value function for the nuisance parameter.
- createFiniteLowerBound(double, double, boolean, double, double, double, boolean) - Method in class org.apache.commons.statistics.distribution.AbstractContinuousDistribution
-
Create a finite lower bound.
- createFiniteUpperBound(double, double, boolean, double, double, double, boolean) - Method in class org.apache.commons.statistics.distribution.AbstractContinuousDistribution
-
Create a finite upper bound.
- createH(double, int) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
Creates
H
of sizem x m
as described in [1]. - createLogBinomialCoefficients(int) - Static method in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Create the natural logarithm of the binomial coefficient for all
k = [0, n]
. - createMappedRankData(double[], DoubleUnaryOperator) - Static method in class org.apache.commons.statistics.ranking.NaturalRanking
-
Creates the rank data.
- createMoment(int) - Method in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
-
Creates the moment constructor for the specified
order
, e.g. - createMoment(int) - Method in class org.apache.commons.statistics.descriptive.IntStatistics.Builder
-
Creates the moment constructor for the specified
order
, e.g. - createMoment(int) - Method in class org.apache.commons.statistics.descriptive.LongStatistics.Builder
-
Creates the moment constructor for the specified
order
, e.g. - createNaNAction(int[]) - Method in class org.apache.commons.statistics.ranking.NaturalRanking
-
Creates the NaN action.
- createNaNTransformer(NaNPolicy, boolean) - Static method in class org.apache.commons.statistics.descriptive.NaNTransformers
- createNonNaNRankData(double[]) - Static method in class org.apache.commons.statistics.ranking.NaturalRanking
-
Creates the rank data with NaNs removed.
- createRankData(double[], int[]) - Method in class org.apache.commons.statistics.ranking.NaturalRanking
-
Creates the rank data.
- createSampler(double[], double[], UniformRandomProvider) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Creates a sampler to sample randomly from the combined distribution of the two samples.
- createSampler(double[], double[], UniformRandomProvider, int) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Creates a sampler to sample randomly from the combined distribution of the two samples.
- createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.AbstractContinuousDistribution
-
Creates a sampler.
- createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.AbstractDiscreteDistribution
-
Creates a sampler.
- createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.BetaDistribution
-
Creates a sampler.
- createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.CauchyDistribution
-
Creates a sampler.
- createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.ChiSquaredDistribution
-
Creates a sampler.
- createSampler(UniformRandomProvider) - Method in interface org.apache.commons.statistics.distribution.ContinuousDistribution
-
Creates a sampler.
- createSampler(UniformRandomProvider) - Method in interface org.apache.commons.statistics.distribution.DiscreteDistribution
-
Creates a sampler.
- createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.ExponentialDistribution
-
Creates a sampler.
- createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.HalfNormalDistribution
- createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.RegularFoldedNormalDistribution
- createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.GammaDistribution
-
Creates a sampler.
- createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.GeometricDistribution
-
Creates a sampler.
- createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.LevyDistribution
-
Creates a sampler.
- createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.LogNormalDistribution
-
Creates a sampler.
- createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.LogUniformDistribution
-
Creates a sampler.
- createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.NakagamiDistribution
- createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.NormalDistribution
-
Creates a sampler.
- createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.ParetoDistribution
-
Creates a sampler.
- createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.PoissonDistribution
-
Creates a sampler.
- createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.TDistribution.NormalTDistribution
- createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.TDistribution.StudentsTDistribution
- createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.DelegatedTrapezoidalDistribution
- createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
Creates a sampler.
- createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.UniformContinuousDistribution
-
Creates a sampler.
- createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.UniformDiscreteDistribution
-
Creates a sampler.
- createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.WeibullDistribution
-
Creates a sampler.
- createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.ZipfDistribution
-
Creates a sampler.
- cumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.BetaDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.CauchyDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.ChiSquaredDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(double) - Method in interface org.apache.commons.statistics.distribution.ContinuousDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.ExponentialDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.FDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.HalfNormalDistribution
- cumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.RegularFoldedNormalDistribution
- cumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.GammaDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.GumbelDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.LaplaceDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.LevyDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.LogisticDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.LogNormalDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.LogUniformDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.NakagamiDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.NormalDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.ParetoDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.TDistribution.NormalTDistribution
- cumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.TDistribution.StudentsTDistribution
- cumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.DelegatedTrapezoidalDistribution
- cumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.RegularTrapezoidalDistribution
- cumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.TriangularDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.UniformContinuousDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.WeibullDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(int) - Method in class org.apache.commons.statistics.distribution.BinomialDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(int) - Method in interface org.apache.commons.statistics.distribution.DiscreteDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(int) - Method in class org.apache.commons.statistics.distribution.GeometricDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(int) - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(int) - Method in class org.apache.commons.statistics.distribution.PascalDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(int) - Method in class org.apache.commons.statistics.distribution.PoissonDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(int) - Method in class org.apache.commons.statistics.distribution.UniformDiscreteDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
. - cumulativeProbability(int) - Method in class org.apache.commons.statistics.distribution.ZipfDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X <= x)
.
D
- d - Variable in class org.apache.commons.statistics.descriptive.UInt128
-
bits 32-1 (low 32-bits).
- d - Variable in class org.apache.commons.statistics.descriptive.UInt192
-
bits 96-65.
- d - Variable in class org.apache.commons.statistics.distribution.TrapezoidalDistribution
-
Upper limit of this distribution (inclusive).
- data - Variable in class org.apache.commons.statistics.inference.SquareMatrixSupport.ArrayRealSquareMatrix
-
Entries of the matrix.
- data - Variable in class org.apache.commons.statistics.inference.UnconditionedExactTest.Candidates
-
Candidate (key,value) pairs.
- data - Variable in class org.apache.commons.statistics.inference.UnconditionedExactTest.XYList
-
The list data.
- data - Variable in class org.apache.commons.statistics.ranking.NaturalRanking.IntList
-
The list data.
- DataDispersion - Enum in org.apache.commons.statistics.inference
-
Represents an assumption on the dispersion of data.
- DataDispersion() - Constructor for enum org.apache.commons.statistics.inference.DataDispersion
- DataPosition(double, int) - Constructor for class org.apache.commons.statistics.ranking.NaturalRanking.DataPosition
-
Create an instance with the given value and position.
- DEFAULT - Static variable in class org.apache.commons.statistics.descriptive.Median
-
Default instance.
- DEFAULT - Static variable in class org.apache.commons.statistics.descriptive.Quantile
-
Default instance.
- DEFAULT - Static variable in class org.apache.commons.statistics.descriptive.StatisticsConfiguration
-
Default instance.
- DEFAULT - Static variable in class org.apache.commons.statistics.inference.BinomialTest
-
Default instance.
- DEFAULT - Static variable in class org.apache.commons.statistics.inference.ChiSquareTest
-
Default instance.
- DEFAULT - Static variable in class org.apache.commons.statistics.inference.FisherExactTest
-
Default instance.
- DEFAULT - Static variable in class org.apache.commons.statistics.inference.GTest
-
Default instance.
- DEFAULT - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Default instance.
- DEFAULT - Static variable in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
Default instance.
- DEFAULT - Static variable in class org.apache.commons.statistics.inference.OneWayAnova
-
Default instance.
- DEFAULT - Static variable in class org.apache.commons.statistics.inference.TTest
-
Default instance.
- DEFAULT - Static variable in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Default instance.
- DEFAULT - Static variable in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Default instance.
- DEFAULT_NAN_STRATEGY - Static variable in class org.apache.commons.statistics.ranking.NaturalRanking
-
Default NaN strategy.
- DEFAULT_TIES_STRATEGY - Static variable in class org.apache.commons.statistics.ranking.NaturalRanking
-
Default ties strategy.
- degreesOfFreedom - Variable in class org.apache.commons.statistics.distribution.TDistribution
-
The degrees of freedom.
- degreesOfFreedom - Variable in class org.apache.commons.statistics.inference.TTest.Result
-
Degrees of freedom.
- degreesOfFreedomAdjustment - Variable in class org.apache.commons.statistics.inference.ChiSquareTest
-
Degrees of freedom adjustment.
- degreesOfFreedomAdjustment - Variable in class org.apache.commons.statistics.inference.GTest
-
Degrees of freedom adjustment.
- delegate - Variable in class org.apache.commons.statistics.descriptive.Sum
-
Sum
used to compute the sum. - delegate - Variable in class org.apache.commons.statistics.descriptive.SumOfLogs
-
Sum
used to compute the sum. - delegate - Variable in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.DelegatedTrapezoidalDistribution
-
Distribution delegate.
- DelegatedTrapezoidalDistribution(double, double, double, double, ContinuousDistribution) - Constructor for class org.apache.commons.statistics.distribution.TrapezoidalDistribution.DelegatedTrapezoidalDistribution
- denominatorDegreesOfFreedom - Variable in class org.apache.commons.statistics.distribution.FDistribution
-
The denominator degrees of freedom.
- density(double) - Method in class org.apache.commons.statistics.distribution.BetaDistribution
-
Returns the probability density function (PDF) of this distribution evaluated at the specified point
x
. - density(double) - Method in class org.apache.commons.statistics.distribution.CauchyDistribution
-
Returns the probability density function (PDF) of this distribution evaluated at the specified point
x
. - density(double) - Method in class org.apache.commons.statistics.distribution.ChiSquaredDistribution
-
Returns the probability density function (PDF) of this distribution evaluated at the specified point
x
. - density(double) - Method in interface org.apache.commons.statistics.distribution.ContinuousDistribution
-
Returns the probability density function (PDF) of this distribution evaluated at the specified point
x
. - density(double) - Method in class org.apache.commons.statistics.distribution.ExponentialDistribution
-
Returns the probability density function (PDF) of this distribution evaluated at the specified point
x
. - density(double) - Method in class org.apache.commons.statistics.distribution.FDistribution
-
Returns the probability density function (PDF) of this distribution evaluated at the specified point
x
. - density(double) - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.HalfNormalDistribution
- density(double) - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.RegularFoldedNormalDistribution
- density(double) - Method in class org.apache.commons.statistics.distribution.GammaDistribution
-
Returns the probability density function (PDF) of this distribution evaluated at the specified point
x
. - density(double) - Method in class org.apache.commons.statistics.distribution.GumbelDistribution
-
Returns the probability density function (PDF) of this distribution evaluated at the specified point
x
. - density(double) - Method in class org.apache.commons.statistics.distribution.LaplaceDistribution
-
Returns the probability density function (PDF) of this distribution evaluated at the specified point
x
. - density(double) - Method in class org.apache.commons.statistics.distribution.LevyDistribution
-
Returns the probability density function (PDF) of this distribution evaluated at the specified point
x
. - density(double) - Method in class org.apache.commons.statistics.distribution.LogisticDistribution
-
Returns the probability density function (PDF) of this distribution evaluated at the specified point
x
. - density(double) - Method in class org.apache.commons.statistics.distribution.LogNormalDistribution
-
Returns the probability density function (PDF) of this distribution evaluated at the specified point
x
. - density(double) - Method in class org.apache.commons.statistics.distribution.LogUniformDistribution
-
Returns the probability density function (PDF) of this distribution evaluated at the specified point
x
. - density(double) - Method in class org.apache.commons.statistics.distribution.NakagamiDistribution
-
Returns the probability density function (PDF) of this distribution evaluated at the specified point
x
. - density(double) - Method in class org.apache.commons.statistics.distribution.NormalDistribution
-
Returns the probability density function (PDF) of this distribution evaluated at the specified point
x
. - density(double) - Method in class org.apache.commons.statistics.distribution.ParetoDistribution
-
Returns the probability density function (PDF) of this distribution evaluated at the specified point
x
. - density(double) - Method in class org.apache.commons.statistics.distribution.TDistribution.NormalTDistribution
- density(double) - Method in class org.apache.commons.statistics.distribution.TDistribution.StudentsTDistribution
- density(double) - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.DelegatedTrapezoidalDistribution
- density(double) - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.RegularTrapezoidalDistribution
- density(double) - Method in class org.apache.commons.statistics.distribution.TriangularDistribution
-
Returns the probability density function (PDF) of this distribution evaluated at the specified point
x
. - density(double) - Method in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
Returns the probability density function (PDF) of this distribution evaluated at the specified point
x
. - density(double) - Method in class org.apache.commons.statistics.distribution.UniformContinuousDistribution
-
Returns the probability density function (PDF) of this distribution evaluated at the specified point
x
. - density(double) - Method in class org.apache.commons.statistics.distribution.WeibullDistribution
-
Returns the probability density function (PDF) of this distribution evaluated at the specified point
x
. - densityNormalisation - Variable in class org.apache.commons.statistics.distribution.TDistribution.StudentsTDistribution
-
Density normalisation factor, sqrt(v) * beta(1/2, v/2), where v = degrees of freedom.
- densityPrefactor - Variable in class org.apache.commons.statistics.distribution.NakagamiDistribution
-
Density prefactor.
- dev - Variable in class org.apache.commons.statistics.descriptive.FirstMoment
-
Half the deviation of most recently added value from the previous first moment.
- dfbg - Variable in class org.apache.commons.statistics.inference.OneWayAnova.Result
-
Degrees of freedom in numerator (between groups).
- dfwg - Variable in class org.apache.commons.statistics.inference.OneWayAnova.Result
-
Degrees of freedom in denominator (within groups).
- dim - Variable in class org.apache.commons.statistics.inference.SquareMatrixSupport.ArrayRealSquareMatrix
-
Dimension.
- dimension() - Method in class org.apache.commons.statistics.inference.SquareMatrixSupport.ArrayRealSquareMatrix
- dimension() - Method in interface org.apache.commons.statistics.inference.SquareMatrixSupport.RealSquareMatrix
-
Gets the dimension for the rows and columns.
- DISABLED - org.apache.commons.statistics.inference.ContinuityCorrection
-
Disable continuity correction.
- DiscreteDistribution - Interface in org.apache.commons.statistics.distribution
-
Interface for distributions on the integers.
- DiscreteDistribution.Sampler - Interface in org.apache.commons.statistics.distribution
-
Distribution sampling functionality.
- DistributionException - Exception in org.apache.commons.statistics.distribution
-
Package private exception class with constants for frequently used messages.
- DistributionException(String, Object...) - Constructor for exception org.apache.commons.statistics.distribution.DistributionException
-
Creates an exception.
- divide(Int128, long) - Static method in class org.apache.commons.statistics.descriptive.IntMath
-
Divide value
x
by the countn
. - divisor - Variable in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.RegularTrapezoidalDistribution
-
Cached value (d + c - a - b).
- divisor1 - Variable in class org.apache.commons.statistics.distribution.TriangularDistribution
-
Cached value ((b - a) * (c - a).
- divisor2 - Variable in class org.apache.commons.statistics.distribution.TriangularDistribution
-
Cached value ((b - a) * (b - c)).
- dmc - Variable in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.RegularTrapezoidalDistribution
-
Cached value (d - c).
- DOUBLE_NOOP - Static variable in class org.apache.commons.statistics.descriptive.Statistics
-
A no-operation double consumer.
- DoubleStatistic - Interface in org.apache.commons.statistics.descriptive
-
Represents a state object for computing a statistic over
double
valued input(s). - DoubleStatistics - Class in org.apache.commons.statistics.descriptive
-
Statistics for
double
values. - DoubleStatistics(long, Min, Max, FirstMoment, Sum, Product, SumOfSquares, SumOfLogs, StatisticsConfiguration) - Constructor for class org.apache.commons.statistics.descriptive.DoubleStatistics
-
Create an instance.
- DoubleStatistics.Builder - Class in org.apache.commons.statistics.descriptive
-
A builder for
DoubleStatistics
. - DOWNSCALE - Static variable in class org.apache.commons.statistics.descriptive.FirstMoment
-
The downscale constant.
- durbinMTW(double, int) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
Computes the Durbin matrix approximation for
P(D_n < d)
using the method of Marsaglia, Tsang and Wang (2003).
E
- e - Variable in class org.apache.commons.statistics.descriptive.UInt192
-
bits 64-33.
- ENABLED - org.apache.commons.statistics.inference.ContinuityCorrection
-
Enable continuity correction.
- eps - Variable in class org.apache.commons.statistics.inference.UnconditionedExactTest.Candidates
-
Relative distance from lowest candidate.
- EPS - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution
-
Machine epsilon, 2^-52.
- EPS_MIN - Static variable in class org.apache.commons.statistics.inference.BracketFinder
-
Tolerance to avoid division by zero.
- equalVariances - Variable in class org.apache.commons.statistics.inference.TTest
-
Assume the two samples have the same population variance.
- ERROR - org.apache.commons.statistics.descriptive.NaNPolicy
-
NaNs result in an exception.
- ErrorNaNTransformer(boolean) - Constructor for class org.apache.commons.statistics.descriptive.NaNTransformers.ErrorNaNTransformer
- ESTIMATE - org.apache.commons.statistics.inference.PValueMethod
-
Use an estimation method for the p-value.
- estimateP(double[], double[], long) - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Estimates the p-value of a two-sample Kolmogorov-Smirnov test evaluating the null hypothesis that
x
andy
are samples drawn from the same probability distribution. - EstimationMethod() - Constructor for enum org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
- estimationType - Variable in class org.apache.commons.statistics.descriptive.Quantile
-
Estimation type used to determine the value from the quantile.
- EULER - Static variable in class org.apache.commons.statistics.distribution.GumbelDistribution
- evaluate(double[]) - Method in class org.apache.commons.statistics.descriptive.Median
-
Evaluate the median.
- evaluate(double[], double) - Method in class org.apache.commons.statistics.descriptive.Quantile
-
Evaluate the
p
-th quantile of the values. - evaluate(double[], double...) - Method in class org.apache.commons.statistics.descriptive.Quantile
-
Evaluate the
p
-th quantiles of the values. - evaluate(int[]) - Method in class org.apache.commons.statistics.descriptive.Median
-
Evaluate the median.
- evaluate(int[], double) - Method in class org.apache.commons.statistics.descriptive.Quantile
-
Evaluate the
p
-th quantile of the values. - evaluate(int[], double...) - Method in class org.apache.commons.statistics.descriptive.Quantile
-
Evaluate the
p
-th quantiles of the values. - evaluate(int, IntToDoubleFunction, double) - Method in class org.apache.commons.statistics.descriptive.Quantile
-
Evaluate the
p
-th quantile of the values. - evaluate(int, IntToDoubleFunction, double...) - Method in class org.apache.commons.statistics.descriptive.Quantile
-
Evaluate the
p
-th quantiles of the values. - evaluations - Variable in class org.apache.commons.statistics.inference.BracketFinder
-
Number of function evaluations performed in the last search.
- evaluations - Variable in class org.apache.commons.statistics.inference.BrentOptimizer
-
The number of function evaluations from the most recent call to optimize.
- EXACT - org.apache.commons.statistics.inference.PValueMethod
-
Use the exact distribution of the test statistic to evaluate the p-value.
- EXACT_LIMIT - Static variable in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Limit on sample size for the exact p-value computation.
- EXACT_STIRLING_ERRORS - Static variable in class org.apache.commons.statistics.distribution.SaddlePointExpansionUtils
-
Exact Stirling expansion error for certain values.
- EXCLUDE - org.apache.commons.statistics.descriptive.NaNPolicy
-
NaNs are excluded from the data.
- ExcludeNaNTransformer(boolean) - Constructor for class org.apache.commons.statistics.descriptive.NaNTransformers.ExcludeNaNTransformer
- exp - Variable in class org.apache.commons.statistics.inference.SquareMatrixSupport.ArrayRealSquareMatrix
-
Matrix scale.
- EXP_BIAS - Static variable in class org.apache.commons.statistics.descriptive.IntMath
-
Bias offset for the exponent of a double.
- EXP_M_HALF_XX_MAX_VALUE - Static variable in class org.apache.commons.statistics.distribution.ExtendedPrecision
-
Approximate x squared value where
exp(-0.5*x*x) == 0
. - EXP_M_HALF_XX_MIN_VALUE - Static variable in class org.apache.commons.statistics.distribution.ExtendedPrecision
-
X squared value where
exp(-0.5*x*x)
cannot increase accuracy using the round-off from x squared. - EXP_SHIFT - Static variable in class org.apache.commons.statistics.descriptive.IntMath
-
Shift for the exponent of a double.
- expmhxx(double) - Static method in class org.apache.commons.statistics.distribution.ExtendedPrecision
-
Compute
exp(-0.5*x*x)
with high accuracy. - exponent - Variable in class org.apache.commons.statistics.distribution.ZipfDistribution
-
Exponent parameter of the distribution.
- ExponentialDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the exponential distribution.
- ExponentialDistribution(double) - Constructor for class org.apache.commons.statistics.distribution.ExponentialDistribution
- expxx(double, double) - Static method in class org.apache.commons.statistics.distribution.ExtendedPrecision
-
Compute
exp(a+b)
with high accuracy assuminga+b = a
. - ExtendedPrecision - Class in org.apache.commons.statistics.distribution
-
Computes extended precision floating-point operations.
- ExtendedPrecision() - Constructor for class org.apache.commons.statistics.distribution.ExtendedPrecision
-
No instances.
F
- f - Variable in class org.apache.commons.statistics.descriptive.UInt192
-
bits 32-1 (low 32-bits).
- FAILED - org.apache.commons.statistics.ranking.NaNStrategy
-
NaNs result in an exception.
- FDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the F-distribution.
- FDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.FDistribution
- fHi - Variable in class org.apache.commons.statistics.inference.BracketFinder
-
Function value at
BracketFinder.hi
. - fill(double[], NaturalRanking.IntList, double) - Static method in class org.apache.commons.statistics.ranking.NaturalRanking
-
Sets
data[i] = value
for each i intiesTrace
. - findExtremeTables(int, int, UnconditionedExactTest.XYList) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Find all tables that are as or more extreme than the observed table.
- findExtremeTablesBoschloo(int, int, int, int, UnconditionedExactTest.XYList) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Find all tables that are as or more extreme than the observed table using the Fisher's p-value as the statistic (also known as Boschloo's test).
- findExtremeTablesZ(int, int, int, int, boolean, UnconditionedExactTest.XYList) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Find all tables that are as or more extreme than the observed table using the Z statistic.
- firstMoment - Variable in class org.apache.commons.statistics.descriptive.Mean
-
First moment used to compute the mean.
- FirstMoment - Class in org.apache.commons.statistics.descriptive
-
Computes the first moment (arithmetic mean) using the definitional formula:
- FirstMoment() - Constructor for class org.apache.commons.statistics.descriptive.FirstMoment
-
Create an instance.
- FirstMoment(double, long) - Constructor for class org.apache.commons.statistics.descriptive.FirstMoment
-
Create an instance with the given first moment.
- FirstMoment(FirstMoment) - Constructor for class org.apache.commons.statistics.descriptive.FirstMoment
-
Copy constructor.
- FisherExactTest - Class in org.apache.commons.statistics.inference
-
Implements Fisher's exact test.
- FisherExactTest(AlternativeHypothesis) - Constructor for class org.apache.commons.statistics.inference.FisherExactTest
- FIXED - org.apache.commons.statistics.ranking.NaNStrategy
-
NaNs are left fixed "in place", that is the rank transformation is applied to the other elements in the input array, but the NaN elements are returned unchanged.
- fLo - Variable in class org.apache.commons.statistics.inference.BracketFinder
-
Function value at
BracketFinder.lo
. - fMid - Variable in class org.apache.commons.statistics.inference.BracketFinder
-
Function value at
BracketFinder.mid
. - fmnk(double[][][], int, int, int) - Static method in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
Compute f(m; n; k), the number of subsets of {0; 1; ...; n} with m elements such that the elements of this subset add up to k.
- FoldedNormalDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the folded normal distribution.
- FoldedNormalDistribution(double) - Constructor for class org.apache.commons.statistics.distribution.FoldedNormalDistribution
- FoldedNormalDistribution.HalfNormalDistribution - Class in org.apache.commons.statistics.distribution
-
Specialisation for the half-normal distribution.
- FoldedNormalDistribution.RegularFoldedNormalDistribution - Class in org.apache.commons.statistics.distribution
-
Regular implementation of the folded normal distribution.
- forEach(Consumer<double[]>) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest.Candidates
-
Perform the given action for each (key, value) pair.
- FOUR_A - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
Factor 4a in the quadratic equation to solve max k: log(2^-52) * 8.
G
- gamma - Variable in class org.apache.commons.statistics.distribution.ChiSquaredDistribution
-
Internal Gamma distribution.
- GammaDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the gamma distribution.
- GammaDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.GammaDistribution
- generalizedHarmonic(int, double) - Static method in class org.apache.commons.statistics.distribution.ZipfDistribution
-
Calculates the Nth generalized harmonic number.
- generalizedHarmonicAscendingSum(int, double) - Static method in class org.apache.commons.statistics.distribution.ZipfDistribution
-
Calculates the Nth generalized harmonic number.
- GEOMETRIC_MEAN - org.apache.commons.statistics.descriptive.Statistic
-
Geometric mean.
- GeometricDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the geometric distribution.
- GeometricDistribution(double) - Constructor for class org.apache.commons.statistics.distribution.GeometricDistribution
- GeometricMean - Class in org.apache.commons.statistics.descriptive
-
Computes the geometric mean of the available values.
- GeometricMean() - Constructor for class org.apache.commons.statistics.descriptive.GeometricMean
-
Create an instance.
- GeometricMean(SumOfLogs, long) - Constructor for class org.apache.commons.statistics.descriptive.GeometricMean
-
Create an instance.
- get(int) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest.XYList
-
Gets the 2D index at the specified
index
. - get(int) - Method in class org.apache.commons.statistics.ranking.NaturalRanking.IntList
-
Gets the element at the specified
index
. - get(int, int) - Method in class org.apache.commons.statistics.inference.SquareMatrixSupport.ArrayRealSquareMatrix
- get(int, int) - Method in interface org.apache.commons.statistics.inference.SquareMatrixSupport.RealSquareMatrix
-
Gets the value.
- getAlpha() - Method in class org.apache.commons.statistics.distribution.BetaDistribution
-
Gets the first shape parameter of this distribution.
- getAsBigInteger() - Method in interface org.apache.commons.statistics.descriptive.BigIntegerStatisticResult
- getAsBigInteger() - Method in class org.apache.commons.statistics.descriptive.IntMax
- getAsBigInteger() - Method in class org.apache.commons.statistics.descriptive.IntMin
- getAsBigInteger() - Method in interface org.apache.commons.statistics.descriptive.IntStatisticResult
- getAsBigInteger() - Method in class org.apache.commons.statistics.descriptive.IntSum
-
Gets the sum of all input values.
- getAsBigInteger() - Method in class org.apache.commons.statistics.descriptive.IntSumOfSquares
-
Gets the sum of squares of all input values.
- getAsBigInteger() - Method in class org.apache.commons.statistics.descriptive.LongMax
- getAsBigInteger() - Method in class org.apache.commons.statistics.descriptive.LongMin
- getAsBigInteger() - Method in interface org.apache.commons.statistics.descriptive.LongStatisticResult
- getAsBigInteger() - Method in class org.apache.commons.statistics.descriptive.LongSum
-
Gets the sum of all input values.
- getAsBigInteger() - Method in class org.apache.commons.statistics.descriptive.LongSumOfSquares
-
Gets the sum of squares of all input values.
- getAsBigInteger() - Method in interface org.apache.commons.statistics.descriptive.StatisticResult
-
Gets a result as a
BigInteger
. - getAsBigInteger(Statistic) - Method in class org.apache.commons.statistics.descriptive.IntStatistics
-
Gets the value of the specified
statistic
as aBigInteger
. - getAsBigInteger(Statistic) - Method in class org.apache.commons.statistics.descriptive.LongStatistics
-
Gets the value of the specified
statistic
as aBigInteger
. - getAsDouble() - Method in interface org.apache.commons.statistics.descriptive.BigIntegerStatisticResult
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.GeometricMean
-
Gets the geometric mean of all input values.
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.IntMax
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.IntMean
-
Gets the mean of all input values.
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.IntMin
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.IntStandardDeviation
-
Gets the standard deviation of all input values.
- getAsDouble() - Method in interface org.apache.commons.statistics.descriptive.IntStatisticResult
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.IntSum
-
Gets the sum of all input values.
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.IntSumOfSquares
-
Gets the sum of squares of all input values.
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.IntVariance
-
Gets the variance of all input values.
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.Kurtosis
-
Gets the kurtosis of all input values.
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.LongMax
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.LongMean
-
Gets the mean of all input values.
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.LongMin
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.LongStandardDeviation
-
Gets the standard deviation of all input values.
- getAsDouble() - Method in interface org.apache.commons.statistics.descriptive.LongStatisticResult
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.LongSum
-
Gets the sum of all input values.
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.LongSumOfSquares
-
Gets the sum of squares of all input values.
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.LongVariance
-
Gets the variance of all input values.
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.Max
-
Gets the maximum of all input values.
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.Mean
-
Gets the mean of all input values.
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.Min
-
Gets the minimum of all input values.
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.Product
-
Gets the product of all input values.
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.Skewness
-
Gets the skewness of all input values.
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.StandardDeviation
-
Gets the standard deviation of all input values.
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.Sum
-
Gets the sum of all input values.
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.SumOfLogs
-
Gets the sum of all input values.
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.SumOfSquares
-
Gets the sum of squares of all input values.
- getAsDouble() - Method in class org.apache.commons.statistics.descriptive.Variance
-
Gets the variance of all input values.
- getAsDouble(Statistic) - Method in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
Gets the value of the specified
statistic
as adouble
. - getAsDouble(Statistic) - Method in class org.apache.commons.statistics.descriptive.IntStatistics
-
Gets the value of the specified
statistic
as adouble
. - getAsDouble(Statistic) - Method in class org.apache.commons.statistics.descriptive.LongStatistics
-
Gets the value of the specified
statistic
as adouble
. - getAsInt() - Method in interface org.apache.commons.statistics.descriptive.BigIntegerStatisticResult
- getAsInt() - Method in class org.apache.commons.statistics.descriptive.IntMax
-
Gets the maximum of all input values.
- getAsInt() - Method in class org.apache.commons.statistics.descriptive.IntMin
-
Gets the minimum of all input values.
- getAsInt() - Method in interface org.apache.commons.statistics.descriptive.IntStatisticResult
- getAsInt() - Method in class org.apache.commons.statistics.descriptive.IntSum
-
Gets the sum of all input values.
- getAsInt() - Method in class org.apache.commons.statistics.descriptive.IntSumOfSquares
-
Gets the sum of squares of all input values.
- getAsInt() - Method in class org.apache.commons.statistics.descriptive.LongMax
-
Gets the maximum of all input values.
- getAsInt() - Method in class org.apache.commons.statistics.descriptive.LongMin
-
Gets the minimum of all input values.
- getAsInt() - Method in interface org.apache.commons.statistics.descriptive.LongStatisticResult
- getAsInt() - Method in class org.apache.commons.statistics.descriptive.LongSum
-
Gets the sum of all input values.
- getAsInt() - Method in class org.apache.commons.statistics.descriptive.LongSumOfSquares
-
Gets the sum of squares of all input values.
- getAsInt() - Method in interface org.apache.commons.statistics.descriptive.StatisticResult
- getAsInt(Statistic) - Method in class org.apache.commons.statistics.descriptive.IntStatistics
-
Gets the value of the specified
statistic
as anint
. - getAsLong() - Method in interface org.apache.commons.statistics.descriptive.BigIntegerStatisticResult
- getAsLong() - Method in class org.apache.commons.statistics.descriptive.IntMax
- getAsLong() - Method in class org.apache.commons.statistics.descriptive.IntMin
- getAsLong() - Method in interface org.apache.commons.statistics.descriptive.IntStatisticResult
- getAsLong() - Method in class org.apache.commons.statistics.descriptive.IntSum
-
Gets the sum of all input values.
- getAsLong() - Method in class org.apache.commons.statistics.descriptive.IntSumOfSquares
-
Gets the sum of squares of all input values.
- getAsLong() - Method in class org.apache.commons.statistics.descriptive.LongMax
-
Gets the maximum of all input values.
- getAsLong() - Method in class org.apache.commons.statistics.descriptive.LongMin
-
Gets the minimum of all input values.
- getAsLong() - Method in interface org.apache.commons.statistics.descriptive.LongStatisticResult
- getAsLong() - Method in class org.apache.commons.statistics.descriptive.LongSum
-
Gets the sum of all input values.
- getAsLong() - Method in class org.apache.commons.statistics.descriptive.LongSumOfSquares
-
Gets the sum of squares of all input values.
- getAsLong() - Method in interface org.apache.commons.statistics.descriptive.StatisticResult
- getAsLong(Statistic) - Method in class org.apache.commons.statistics.descriptive.IntStatistics
-
Gets the value of the specified
statistic
as along
. - getAsLong(Statistic) - Method in class org.apache.commons.statistics.descriptive.LongStatistics
-
Gets the value of the specified
statistic
as along
. - getB() - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution
-
Gets the start of the constant region of the density function.
- getBeta() - Method in class org.apache.commons.statistics.distribution.BetaDistribution
-
Gets the second shape parameter of this distribution.
- getC() - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution
-
Gets the end of the constant region of the density function.
- getCount() - Method in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
Return the count of values recorded.
- getCount() - Method in class org.apache.commons.statistics.descriptive.IntStatistics
-
Return the count of values recorded.
- getCount() - Method in class org.apache.commons.statistics.descriptive.LongStatistics
-
Return the count of values recorded.
- getDegreesOfFreedom() - Method in class org.apache.commons.statistics.distribution.ChiSquaredDistribution
-
Gets the degrees of freedom parameter of this distribution.
- getDegreesOfFreedom() - Method in class org.apache.commons.statistics.distribution.TDistribution
-
Gets the degrees of freedom parameter of this distribution.
- getDegreesOfFreedom() - Method in class org.apache.commons.statistics.inference.TTest.Result
-
Gets the degrees of freedom.
- getDenominatorDegreesOfFreedom() - Method in class org.apache.commons.statistics.distribution.FDistribution
-
Gets the denominator degrees of freedom parameter of this distribution.
- getDeviancePart(int, double) - Static method in class org.apache.commons.statistics.distribution.SaddlePointExpansionUtils
-
A part of the deviance portion of the saddle point approximation.
- getDFBG() - Method in class org.apache.commons.statistics.inference.OneWayAnova.Result
-
Gets the degrees of freedom in the numerator (between groups).
- getDFWG() - Method in class org.apache.commons.statistics.inference.OneWayAnova.Result
-
Gets the degrees of freedom in the denominator (within groups).
- getEvaluations() - Method in class org.apache.commons.statistics.inference.BracketFinder
- getEvaluations() - Method in class org.apache.commons.statistics.inference.BrentOptimizer
-
Gets the number of function evaluations from the most recent call to
optimize
. - getExponent() - Method in class org.apache.commons.statistics.distribution.ZipfDistribution
-
Gets the exponent parameter of this distribution.
- getF(int, int, int) - Static method in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
Gets the storage for f(m, n, k).
- getFHi() - Method in class org.apache.commons.statistics.inference.BracketFinder
-
Get function value at
BracketFinder.getHi()
. - getFirstMoment() - Method in class org.apache.commons.statistics.descriptive.FirstMoment
-
Gets the first moment of all input values.
- getFirstMomentDifference(FirstMoment) - Method in class org.apache.commons.statistics.descriptive.FirstMoment
-
Gets the difference of the first moment between
this
moment and theother
moment. - getFirstMomentHalfDifference(FirstMoment) - Method in class org.apache.commons.statistics.descriptive.FirstMoment
-
Gets the half the difference of the first moment between
this
moment and theother
moment. - getFLo() - Method in class org.apache.commons.statistics.inference.BracketFinder
-
Get function value at
BracketFinder.getLo()
. - getFMid() - Method in class org.apache.commons.statistics.inference.BracketFinder
-
Get function value at
BracketFinder.getMid()
. - getGeometricMean() - Method in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
Gets the geometric mean.
- getGeometricMean() - Method in class org.apache.commons.statistics.descriptive.IntStatistics
-
Gets the geometric mean.
- getGeometricMean() - Method in class org.apache.commons.statistics.descriptive.LongStatistics
-
Gets the geometric mean.
- getHi() - Method in class org.apache.commons.statistics.inference.BracketFinder
- getKurtosis() - Method in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
Gets the kurtosis.
- getKurtosis() - Method in class org.apache.commons.statistics.descriptive.IntStatistics
-
Gets the kurtosis.
- getKurtosis() - Method in class org.apache.commons.statistics.descriptive.LongStatistics
-
Gets the kurtosis.
- getLo() - Method in class org.apache.commons.statistics.inference.BracketFinder
- getLocation() - Method in class org.apache.commons.statistics.distribution.CauchyDistribution
-
Gets the location parameter of this distribution.
- getLocation() - Method in class org.apache.commons.statistics.distribution.GumbelDistribution
-
Gets the location parameter of this distribution.
- getLocation() - Method in class org.apache.commons.statistics.distribution.LaplaceDistribution
-
Gets the location parameter of this distribution.
- getLocation() - Method in class org.apache.commons.statistics.distribution.LevyDistribution
-
Gets the location parameter of this distribution.
- getLocation() - Method in class org.apache.commons.statistics.distribution.LogisticDistribution
-
Gets the location parameter of this distribution.
- getLowerDomain(int, int, int) - Static method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
Return the lowest domain value for the given hypergeometric distribution parameters.
- getLowerMode() - Method in class org.apache.commons.statistics.inference.Hypergeom
-
Get the lower mode of the distribution.
- getMaxX() - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest.XYList
-
Gets the maximum X value (inclusive).
- getMaxY() - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest.XYList
-
Gets the maximum Y value (inclusive).
- getMean() - Method in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
Gets the mean.
- getMean() - Method in class org.apache.commons.statistics.descriptive.IntStatistics
-
Gets the mean.
- getMean() - Method in class org.apache.commons.statistics.descriptive.LongStatistics
-
Gets the mean.
- getMean() - Method in class org.apache.commons.statistics.distribution.BetaDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.BinomialDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.CauchyDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.ChiSquaredDistribution
-
Gets the mean of this distribution.
- getMean() - Method in interface org.apache.commons.statistics.distribution.ContinuousDistribution
-
Gets the mean of this distribution.
- getMean() - Method in interface org.apache.commons.statistics.distribution.DiscreteDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.ExponentialDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.FDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.HalfNormalDistribution
- getMean() - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.RegularFoldedNormalDistribution
- getMean() - Method in class org.apache.commons.statistics.distribution.GammaDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.GeometricDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.GumbelDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.LaplaceDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.LevyDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.LogisticDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.LogNormalDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.LogUniformDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.NakagamiDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.NormalDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.ParetoDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.PascalDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.PoissonDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.TDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.TDistribution.NormalTDistribution
- getMean() - Method in class org.apache.commons.statistics.distribution.TDistribution.StudentsTDistribution
- getMean() - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.DelegatedTrapezoidalDistribution
- getMean() - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.RegularTrapezoidalDistribution
- getMean() - Method in class org.apache.commons.statistics.distribution.TriangularDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.UniformContinuousDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.UniformDiscreteDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.WeibullDistribution
-
Gets the mean of this distribution.
- getMean() - Method in class org.apache.commons.statistics.distribution.ZipfDistribution
-
Gets the mean of this distribution.
- getMedian() - Method in class org.apache.commons.statistics.distribution.AbstractContinuousDistribution
-
Gets the median.
- getMedian() - Method in class org.apache.commons.statistics.distribution.AbstractDiscreteDistribution
-
Gets the median.
- getMedian() - Method in class org.apache.commons.statistics.distribution.BinomialDistribution
-
Gets the median.
- getMedian() - Method in class org.apache.commons.statistics.distribution.CauchyDistribution
-
Gets the median.
- getMedian() - Method in class org.apache.commons.statistics.distribution.ExponentialDistribution
-
Gets the median.
- getMedian() - Method in class org.apache.commons.statistics.distribution.GumbelDistribution
-
Gets the median.
- getMedian() - Method in class org.apache.commons.statistics.distribution.LaplaceDistribution
-
Gets the median.
- getMedian() - Method in class org.apache.commons.statistics.distribution.LevyDistribution
-
Gets the median.
- getMedian() - Method in class org.apache.commons.statistics.distribution.LogisticDistribution
-
Gets the median.
- getMedian() - Method in class org.apache.commons.statistics.distribution.LogUniformDistribution
-
Gets the median.
- getMedian() - Method in class org.apache.commons.statistics.distribution.TDistribution.StudentsTDistribution
- getMid() - Method in class org.apache.commons.statistics.inference.BracketFinder
- getMidPoint() - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
Return the mid-point
x
of the distribution, and the cdf(x). - getMinimum() - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest.Candidates
-
Return the minimum (key,value) pair.
- getMode() - Method in class org.apache.commons.statistics.distribution.TriangularDistribution
-
Gets the mode parameter of this distribution.
- getMSBG() - Method in class org.apache.commons.statistics.inference.OneWayAnova.Result
-
Gets the mean square between groups.
- getMSWG() - Method in class org.apache.commons.statistics.inference.OneWayAnova.Result
-
Gets the mean square within groups.
- getMu() - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution
-
Gets the location parameter \( \mu \) of this distribution.
- getMu() - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.HalfNormalDistribution
- getMu() - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.RegularFoldedNormalDistribution
- getMu() - Method in class org.apache.commons.statistics.distribution.LogNormalDistribution
-
Gets the
mu
parameter of this distribution. - getNanStrategy() - Method in class org.apache.commons.statistics.ranking.NaturalRanking
-
Return the
NaNStrategy
. - getNuisanceParameter() - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest.Result
-
Gets the nuisance parameter that maximised the probability sum of the as or more extreme tables.
- getNumberOfElements() - Method in class org.apache.commons.statistics.distribution.ZipfDistribution
-
Gets the number of elements parameter of this distribution.
- getNumberOfSuccesses() - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
Gets the number of successes parameter of this distribution.
- getNumberOfSuccesses() - Method in class org.apache.commons.statistics.distribution.PascalDistribution
-
Gets the number of successes parameter of this distribution.
- getNumberOfTrials() - Method in class org.apache.commons.statistics.distribution.BinomialDistribution
-
Gets the number of trials parameter of this distribution.
- getNumeratorDegreesOfFreedom() - Method in class org.apache.commons.statistics.distribution.FDistribution
-
Gets the numerator degrees of freedom parameter of this distribution.
- getPoint() - Method in class org.apache.commons.statistics.inference.BrentOptimizer.PointValuePair
-
Get the point.
- getPopulationSize() - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
Gets the population size parameter of this distribution.
- getPosition() - Method in class org.apache.commons.statistics.ranking.NaturalRanking.DataPosition
-
Returns the data position.
- getProbabilityOfSuccess() - Method in class org.apache.commons.statistics.distribution.BinomialDistribution
-
Gets the probability of success parameter of this distribution.
- getProbabilityOfSuccess() - Method in class org.apache.commons.statistics.distribution.GeometricDistribution
-
Gets the probability of success parameter of this distribution.
- getProbabilityOfSuccess() - Method in class org.apache.commons.statistics.distribution.PascalDistribution
-
Gets the probability of success parameter of this distribution.
- getPValue() - Method in class org.apache.commons.statistics.inference.BaseSignificanceResult
- getPValue() - Method in interface org.apache.commons.statistics.inference.SignificanceResult
-
Returns the test statistic p-value.
- getRandomIntFunction() - Method in class org.apache.commons.statistics.ranking.NaturalRanking
-
Gets the function to map positive
x
randomly to[0, x)
. - getResult(Statistic) - Method in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
Gets a supplier for the value of the specified
statistic
. - getResult(Statistic) - Method in class org.apache.commons.statistics.descriptive.IntStatistics
-
Gets a supplier for the value of the specified
statistic
. - getResult(Statistic) - Method in class org.apache.commons.statistics.descriptive.LongStatistics
-
Gets a supplier for the value of the specified
statistic
. - getResultAsBigIntegerOrNull(StatisticResult) - Static method in class org.apache.commons.statistics.descriptive.Statistics
-
Gets the statistic result using the
BigInteger
value. - getResultAsDoubleOrNull(StatisticResult) - Static method in class org.apache.commons.statistics.descriptive.Statistics
-
Gets the statistic result using the
double
value. - getResultAsIntOrNull(StatisticResult) - Static method in class org.apache.commons.statistics.descriptive.Statistics
-
Gets the statistic result using the
int
value. - getResultAsLongOrNull(StatisticResult) - Static method in class org.apache.commons.statistics.descriptive.Statistics
-
Gets the statistic result using the
long
value. - getSampleSize() - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
Gets the sample size parameter of this distribution.
- getScale() - Method in class org.apache.commons.statistics.distribution.CauchyDistribution
-
Gets the scale parameter of this distribution.
- getScale() - Method in class org.apache.commons.statistics.distribution.GammaDistribution
-
Gets the scale parameter of this distribution.
- getScale() - Method in class org.apache.commons.statistics.distribution.GumbelDistribution
-
Gets the scale parameter of this distribution.
- getScale() - Method in class org.apache.commons.statistics.distribution.LaplaceDistribution
-
Gets the scale parameter of this distribution.
- getScale() - Method in class org.apache.commons.statistics.distribution.LevyDistribution
-
Gets the scale parameter of this distribution.
- getScale() - Method in class org.apache.commons.statistics.distribution.LogisticDistribution
-
Gets the scale parameter of this distribution.
- getScale() - Method in class org.apache.commons.statistics.distribution.NakagamiDistribution
-
Gets the scale parameter of this distribution.
- getScale() - Method in class org.apache.commons.statistics.distribution.ParetoDistribution
-
Gets the scale parameter of this distribution.
- getScale() - Method in class org.apache.commons.statistics.distribution.WeibullDistribution
-
Gets the scale parameter of this distribution.
- getShape() - Method in class org.apache.commons.statistics.distribution.GammaDistribution
-
Gets the shape parameter of this distribution.
- getShape() - Method in class org.apache.commons.statistics.distribution.NakagamiDistribution
-
Gets the shape parameter of this distribution.
- getShape() - Method in class org.apache.commons.statistics.distribution.ParetoDistribution
-
Gets the shape parameter of this distribution.
- getShape() - Method in class org.apache.commons.statistics.distribution.WeibullDistribution
-
Gets the shape parameter of this distribution.
- getSigma() - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution
-
Gets the scale parameter \( \sigma \) of this distribution.
- getSigma() - Method in class org.apache.commons.statistics.distribution.LogNormalDistribution
-
Gets the
sigma
parameter of this distribution. - getSign() - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest.OneResult
-
Gets the sign of the statistic.
- getSkewness() - Method in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
Gets the skewness.
- getSkewness() - Method in class org.apache.commons.statistics.descriptive.IntStatistics
-
Gets the skewness.
- getSkewness() - Method in class org.apache.commons.statistics.descriptive.LongStatistics
-
Gets the skewness.
- getStandardDeviation() - Method in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
Gets the standard deviation.
- getStandardDeviation() - Method in class org.apache.commons.statistics.descriptive.IntStatistics
-
Gets the standard deviation.
- getStandardDeviation() - Method in class org.apache.commons.statistics.descriptive.LongStatistics
-
Gets the standard deviation.
- getStandardDeviation() - Method in class org.apache.commons.statistics.distribution.NormalDistribution
-
Gets the standard deviation parameter of this distribution.
- getStatistic() - Method in class org.apache.commons.statistics.inference.BaseSignificanceResult
- getStatistic() - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest.TwoResult
-
Returns the test statistic.
- getStatistic() - Method in class org.apache.commons.statistics.inference.MannWhitneyUTest.Result
-
Returns the test statistic.
- getStatistic() - Method in interface org.apache.commons.statistics.inference.SignificanceResult
-
Returns the test statistic.
- getStatistic() - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest.Result
-
Returns the test statistic.
- getStirlingError(int) - Static method in class org.apache.commons.statistics.distribution.SaddlePointExpansionUtils
-
Compute the error of Stirling's series at the given value.
- getSum() - Method in class org.apache.commons.statistics.descriptive.IntSum
-
Gets the sum.
- getSum() - Method in class org.apache.commons.statistics.descriptive.LongSum
-
Gets the sum.
- getSumOfCubedDeviations() - Method in class org.apache.commons.statistics.descriptive.SumOfCubedDeviations
-
Gets the sum of cubed deviations of all input values.
- getSumOfFourthDeviations() - Method in class org.apache.commons.statistics.descriptive.SumOfFourthDeviations
-
Gets the sum of fourth deviations of all input values.
- getSumOfSquaredDeviations() - Method in class org.apache.commons.statistics.descriptive.SumOfSquaredDeviations
-
Gets the sum of squared deviations of all input values.
- getSumOfSquares() - Method in class org.apache.commons.statistics.descriptive.IntSumOfSquares
-
Gets the sum of squares.
- getSumOfSquares() - Method in class org.apache.commons.statistics.descriptive.LongSumOfSquares
-
Gets the sum of squares.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.BetaDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.BinomialDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.CauchyDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.ChiSquaredDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in interface org.apache.commons.statistics.distribution.ContinuousDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in interface org.apache.commons.statistics.distribution.DiscreteDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.ExponentialDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.FDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.GammaDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.GeometricDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.GumbelDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.LaplaceDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.LevyDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.LogisticDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.LogNormalDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.LogUniformDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.NakagamiDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.NormalDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.ParetoDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.PascalDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.PoissonDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.TDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.TriangularDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.UniformContinuousDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.UniformDiscreteDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.WeibullDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.distribution.ZipfDistribution
-
Gets the lower bound of the support.
- getSupportLowerBound() - Method in class org.apache.commons.statistics.inference.Hypergeom
-
Get the lower bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.BetaDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.BinomialDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.CauchyDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.ChiSquaredDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in interface org.apache.commons.statistics.distribution.ContinuousDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in interface org.apache.commons.statistics.distribution.DiscreteDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.ExponentialDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.FDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.GammaDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.GeometricDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.GumbelDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.LaplaceDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.LevyDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.LogisticDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.LogNormalDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.LogUniformDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.NakagamiDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.NormalDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.ParetoDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.PascalDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.PoissonDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.TDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.TriangularDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.UniformContinuousDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.UniformDiscreteDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.WeibullDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.distribution.ZipfDistribution
-
Gets the upper bound of the support.
- getSupportUpperBound() - Method in class org.apache.commons.statistics.inference.Hypergeom
-
Get the upper bound of the support.
- getTiesStrategy() - Method in class org.apache.commons.statistics.ranking.NaturalRanking
-
Return the
TiesStrategy
. - getUpperD() - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest.TwoResult
-
Return the upper bound of the D statistic from all possible paths through regions with ties.
- getUpperDomain(int, int) - Static method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
Return the highest domain value for the given hypergeometric distribution parameters.
- getUpperMode() - Method in class org.apache.commons.statistics.inference.Hypergeom
-
Get the upper mode of the distribution.
- getUpperPValue() - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest.TwoResult
-
Return the p-value of the upper bound of the D statistic.
- getValue() - Method in class org.apache.commons.statistics.inference.BrentOptimizer.PointValuePair
-
Get the value of the objective function.
- getVariance() - Method in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
Gets the variance.
- getVariance() - Method in class org.apache.commons.statistics.descriptive.IntStatistics
-
Gets the variance.
- getVariance() - Method in class org.apache.commons.statistics.descriptive.LongStatistics
-
Gets the variance.
- getVariance() - Method in class org.apache.commons.statistics.distribution.BetaDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.BinomialDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.CauchyDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.ChiSquaredDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in interface org.apache.commons.statistics.distribution.ContinuousDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in interface org.apache.commons.statistics.distribution.DiscreteDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.ExponentialDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.FDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.HalfNormalDistribution
- getVariance() - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.RegularFoldedNormalDistribution
- getVariance() - Method in class org.apache.commons.statistics.distribution.GammaDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.GeometricDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.GumbelDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.LaplaceDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.LevyDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.LogisticDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.LogNormalDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.LogUniformDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.NakagamiDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.NormalDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.ParetoDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.PascalDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.PoissonDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.TDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.TDistribution.NormalTDistribution
- getVariance() - Method in class org.apache.commons.statistics.distribution.TDistribution.StudentsTDistribution
- getVariance() - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.DelegatedTrapezoidalDistribution
- getVariance() - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.RegularTrapezoidalDistribution
- getVariance() - Method in class org.apache.commons.statistics.distribution.TriangularDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.UniformContinuousDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.UniformDiscreteDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.WeibullDistribution
-
Gets the variance of this distribution.
- getVariance() - Method in class org.apache.commons.statistics.distribution.ZipfDistribution
-
Gets the variance of this distribution.
- getVarianceOrStd(boolean) - Method in class org.apache.commons.statistics.descriptive.IntStatistics
-
Gets the variance or standard deviation.
- getVarianceOrStd(boolean) - Method in class org.apache.commons.statistics.descriptive.LongStatistics
-
Gets the variance or standard deviation.
- getVCBG() - Method in class org.apache.commons.statistics.inference.OneWayAnova.Result
-
Gets the variance component between groups.
- getVCWG() - Method in class org.apache.commons.statistics.inference.OneWayAnova.Result
-
Gets the variance component within groups.
- getWidth() - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest.XYList
-
Gets the width.
- GOLD - Static variable in class org.apache.commons.statistics.inference.BracketFinder
-
Golden section.
- GOLDEN_SECTION - Static variable in class org.apache.commons.statistics.inference.BrentOptimizer
-
Golden section.
- GREATER_THAN - org.apache.commons.statistics.inference.AlternativeHypothesis
-
Represents a right-sided test.
- growLimit - Variable in class org.apache.commons.statistics.inference.BracketFinder
-
Factor for expanding the interval.
- GTest - Class in org.apache.commons.statistics.inference
-
Implements G-test (Generalized Log-Likelihood Ratio Test) statistics.
- GTest(int) - Constructor for class org.apache.commons.statistics.inference.GTest
- GumbelDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the Gumbel distribution.
- GumbelDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.GumbelDistribution
H
- HALF - Static variable in class org.apache.commons.statistics.descriptive.IntMath
-
0.5.
- HALF - Static variable in class org.apache.commons.statistics.distribution.BinomialDistribution
-
1/2.
- HALF - Static variable in class org.apache.commons.statistics.distribution.GeometricDistribution
-
1/2.
- HALF - Static variable in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
1/2.
- HALF - Static variable in class org.apache.commons.statistics.inference.Hypergeom
-
1/2.
- HALF - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
1/2.
- HALF_LOG_TWO_PI - Static variable in class org.apache.commons.statistics.distribution.Constants
-
0.5 * ln(2 pi).
- HALF_OVER_ERFCINV_HALF_SQUARED - Static variable in class org.apache.commons.statistics.distribution.LevyDistribution
-
1 / 2(erfc^-1 (0.5))^2.
- halfC - Variable in class org.apache.commons.statistics.distribution.LevyDistribution
-
Half of c (for calculations).
- HalfNormalDistribution(double) - Constructor for class org.apache.commons.statistics.distribution.FoldedNormalDistribution.HalfNormalDistribution
- hasSignificantTies() - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest.TwoResult
-
Returns
true
if there were ties between samples that occurred in a region which could change the D statistic if the ties were resolved to a defined order. - hasTiedValues() - Method in class org.apache.commons.statistics.inference.MannWhitneyUTest.Result
-
Return
true
if the data had tied values. - hasTiedValues() - Method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest.Result
-
Return
true
if the data had tied values (with equal ranks). - hasZeroValues() - Method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest.Result
-
Return
true
if the data had zero values. - HETEROSCEDASTIC - org.apache.commons.statistics.inference.DataDispersion
-
Data does not have the same variance.
- HF1 - org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
-
Inverse of the empirical distribution function.
- HF2 - org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
-
Similar to
Quantile.EstimationMethod.HF1
with averaging at discontinuities. - HF3 - org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
-
The observation closest to \( np \).
- HF4 - org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
-
Linear interpolation of the inverse of the empirical CDF.
- HF5 - org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
-
A piecewise linear function where the knots are the values midway through the steps of the empirical CDF.
- HF6 - org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
-
Linear interpolation of the expectations for the order statistics for the uniform distribution on [0,1].
- HF7 - org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
-
Linear interpolation of the modes for the order statistics for the uniform distribution on [0,1].
- HF8 - org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
-
Linear interpolation of the approximate medians for order statistics.
- HF9 - org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
-
Quantile estimates are approximately unbiased for the expected order statistics if \( x \) is normally distributed.
- hi - Variable in class org.apache.commons.statistics.descriptive.Int128
-
high 64-bits.
- hi - Variable in class org.apache.commons.statistics.inference.BracketFinder
-
Higher bound of the bracket.
- hi64() - Method in class org.apache.commons.statistics.descriptive.Int128
-
Return the higher 64-bits as a
long
value. - hi64() - Method in class org.apache.commons.statistics.descriptive.UInt128
-
Return the higher 64-bits as a
long
value. - hi64() - Method in class org.apache.commons.statistics.descriptive.UInt192
-
Return the higher 64-bits as a
long
value. - hi64() - Method in class org.apache.commons.statistics.descriptive.UInt96
-
Return the higher 64-bits as a
long
value. - HOMOSCEDASTIC - org.apache.commons.statistics.inference.DataDispersion
-
All data has the same finite variance (homogeneity of variance).
- Hypergeom - Class in org.apache.commons.statistics.inference
-
Provide a wrapper around the
HypergeometricDistribution
that caches all probability mass values. - Hypergeom(int, int, int) - Constructor for class org.apache.commons.statistics.inference.Hypergeom
- HypergeometricDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the hypergeometric distribution.
- HypergeometricDistribution(int, int, int) - Constructor for class org.apache.commons.statistics.distribution.HypergeometricDistribution
I
- identity() - Method in class org.apache.commons.statistics.inference.SquareMatrixSupport.ArrayRealSquareMatrix
-
Creates the identity matrix I with the same dimension as
this
. - IGNORED_D - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Placeholder to use for the two-sample ties D array when the value can be ignored.
- IGNORED_SIGN - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Placeholder to use for the two-sample sign array when the value can be ignored.
- INC_FRACTION - Static variable in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Fraction of the increment (interval between enumerated points) to initialise the bracket for the minima.
- INCLUDE - org.apache.commons.statistics.descriptive.NaNPolicy
-
NaNs are included in the data.
- IncludeNaNTransformer(boolean) - Constructor for class org.apache.commons.statistics.descriptive.NaNTransformers.IncludeNaNTransformer
- INCOMPATIBLE_STATISTICS - Static variable in class org.apache.commons.statistics.descriptive.Statistics
-
Error message for an incompatible statistics.
- index(double, int) - Method in enum org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
-
Finds the index
i
and fractional partg
of a real-valued position to interpolate the quantile. - Inequality - Enum in org.apache.commons.statistics.inference
-
Represents a non-equal comparison between two numbers.
- Inequality() - Constructor for enum org.apache.commons.statistics.inference.Inequality
- InferenceException - Exception in org.apache.commons.statistics.inference
-
Package private exception class with constants for frequently used messages.
- InferenceException(String) - Constructor for exception org.apache.commons.statistics.inference.InferenceException
-
Creates an exception.
- InferenceException(String, Object...) - Constructor for exception org.apache.commons.statistics.inference.InferenceException
-
Creates an exception.
- initialize(double[]) - Static method in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
Initialize the array for f(m, n, x).
- innerCumulativeProbability(int, int) - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
For this distribution,
X
, this method returnsP(x0 <= X <= x1)
. - innerCumulativeProbability(int, int) - Method in class org.apache.commons.statistics.inference.Hypergeom
-
For this distribution,
X
, this method returnsP(x0 <= X <= x1)
. - INT_NOOP - Static variable in class org.apache.commons.statistics.descriptive.Statistics
-
A no-operation int consumer.
- Int128 - Class in org.apache.commons.statistics.descriptive
-
A mutable 128-bit signed integer.
- Int128() - Constructor for class org.apache.commons.statistics.descriptive.Int128
-
Create an instance.
- Int128(long) - Constructor for class org.apache.commons.statistics.descriptive.Int128
-
Create an instance.
- Int128(long, long) - Constructor for class org.apache.commons.statistics.descriptive.Int128
-
Create an instance using a direct binary representation.
- interpolate(double, double, double) - Static method in class org.apache.commons.statistics.descriptive.Interpolation
-
Linear interpolation between sorted values
a <= b
using the interpolantt
taking care to avoid overflow. - Interpolation - Class in org.apache.commons.statistics.descriptive
-
Support class for interpolation.
- Interpolation() - Constructor for class org.apache.commons.statistics.descriptive.Interpolation
-
No instances.
- IntList(int) - Constructor for class org.apache.commons.statistics.ranking.NaturalRanking.IntList
- IntMath - Class in org.apache.commons.statistics.descriptive
-
Support class for integer math.
- IntMath() - Constructor for class org.apache.commons.statistics.descriptive.IntMath
-
No instances.
- IntMax - Class in org.apache.commons.statistics.descriptive
-
Returns the maximum of the available values.
- IntMax() - Constructor for class org.apache.commons.statistics.descriptive.IntMax
-
Create an instance.
- IntMean - Class in org.apache.commons.statistics.descriptive
-
Computes the arithmetic mean of the available values.
- IntMean() - Constructor for class org.apache.commons.statistics.descriptive.IntMean
-
Create an instance.
- IntMean(Int128, int) - Constructor for class org.apache.commons.statistics.descriptive.IntMean
-
Create an instance.
- IntMin - Class in org.apache.commons.statistics.descriptive
-
Returns the minimum of the available values.
- IntMin() - Constructor for class org.apache.commons.statistics.descriptive.IntMin
-
Create an instance.
- IntStandardDeviation - Class in org.apache.commons.statistics.descriptive
-
Computes the standard deviation of the available values.
- IntStandardDeviation() - Constructor for class org.apache.commons.statistics.descriptive.IntStandardDeviation
-
Create an instance.
- IntStandardDeviation(UInt128, Int128, int) - Constructor for class org.apache.commons.statistics.descriptive.IntStandardDeviation
-
Create an instance.
- IntStatistic - Interface in org.apache.commons.statistics.descriptive
-
Represents a state object for computing a statistic over
int
valued input(s). - IntStatisticResult - Interface in org.apache.commons.statistics.descriptive
-
Represents the
int
result of a statistic computed over a set of values. - IntStatistics - Class in org.apache.commons.statistics.descriptive
-
Statistics for
int
values. - IntStatistics(long, IntMin, IntMax, FirstMoment, IntSum, Product, IntSumOfSquares, SumOfLogs, StatisticsConfiguration) - Constructor for class org.apache.commons.statistics.descriptive.IntStatistics
-
Create an instance.
- IntStatistics.Builder - Class in org.apache.commons.statistics.descriptive
-
A builder for
IntStatistics
. - IntSum - Class in org.apache.commons.statistics.descriptive
-
Returns the sum of the available values.
- IntSum() - Constructor for class org.apache.commons.statistics.descriptive.IntSum
-
Create an instance.
- IntSum(Int128) - Constructor for class org.apache.commons.statistics.descriptive.IntSum
-
Create an instance.
- IntSumOfSquares - Class in org.apache.commons.statistics.descriptive
-
Returns the sum of the squares of the available values.
- IntSumOfSquares() - Constructor for class org.apache.commons.statistics.descriptive.IntSumOfSquares
-
Create an instance.
- IntSumOfSquares(UInt128) - Constructor for class org.apache.commons.statistics.descriptive.IntSumOfSquares
-
Create an instance.
- IntVariance - Class in org.apache.commons.statistics.descriptive
-
Computes the variance of the available values.
- IntVariance() - Constructor for class org.apache.commons.statistics.descriptive.IntVariance
-
Create an instance.
- IntVariance(UInt128, Int128, int) - Constructor for class org.apache.commons.statistics.descriptive.IntVariance
-
Create an instance.
- INVALID_NON_ZERO_PROBABILITY - Static variable in exception org.apache.commons.statistics.distribution.DistributionException
-
Error message for "invalid non-zero probability" condition when "x not in (0, 1]".
- INVALID_NUMBER_OF_PROBABILITIES - Static variable in class org.apache.commons.statistics.descriptive.Quantile
-
Message when the number of probabilities in a range is not valid.
- INVALID_PROBABILITY - Static variable in class org.apache.commons.statistics.descriptive.Quantile
-
Message when the probability is not in the range
[0, 1]
. - INVALID_PROBABILITY - Static variable in exception org.apache.commons.statistics.distribution.DistributionException
-
Error message for "invalid probability" condition when "x not in [0, 1]".
- INVALID_PROBABILITY - Static variable in exception org.apache.commons.statistics.inference.InferenceException
-
Error message for "invalid probability" condition when "x not in [0, 1]".
- INVALID_RANGE_LOW_GT_HIGH - Static variable in exception org.apache.commons.statistics.distribution.DistributionException
-
Error message for "invalid range" condition when "lower > upper".
- INVALID_RANGE_LOW_GTE_HIGH - Static variable in exception org.apache.commons.statistics.distribution.DistributionException
-
Error message for "invalid range" condition when "lower >= upper".
- INVALID_SIGNIFICANCE - Static variable in exception org.apache.commons.statistics.inference.InferenceException
-
Error message for "invalid significance" condition when "x not in (0, 0.5]".
- INVALID_SIZE - Static variable in class org.apache.commons.statistics.descriptive.Quantile
-
Message when the size is not valid.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.AbstractContinuousDistribution
-
Computes the quantile function of this distribution.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.AbstractDiscreteDistribution
-
Computes the quantile function of this distribution.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.CauchyDistribution
-
Computes the quantile function of this distribution.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.ChiSquaredDistribution
-
Computes the quantile function of this distribution.
- inverseCumulativeProbability(double) - Method in interface org.apache.commons.statistics.distribution.ContinuousDistribution
-
Computes the quantile function of this distribution.
- inverseCumulativeProbability(double) - Method in interface org.apache.commons.statistics.distribution.DiscreteDistribution
-
Computes the quantile function of this distribution.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.ExponentialDistribution
-
Computes the quantile function of this distribution.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.HalfNormalDistribution
- inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.GeometricDistribution
-
Computes the quantile function of this distribution.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.GumbelDistribution
-
Computes the quantile function of this distribution.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
- inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.LaplaceDistribution
-
Computes the quantile function of this distribution.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.LevyDistribution
-
Computes the quantile function of this distribution.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.LogisticDistribution
-
Computes the quantile function of this distribution.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.LogNormalDistribution
-
Computes the quantile function of this distribution.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.LogUniformDistribution
-
Computes the quantile function of this distribution.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.NormalDistribution
-
Computes the quantile function of this distribution.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.ParetoDistribution
-
Computes the quantile function of this distribution.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.TDistribution.NormalTDistribution
- inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.DelegatedTrapezoidalDistribution
- inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.RegularTrapezoidalDistribution
- inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.TriangularDistribution
-
Computes the quantile function of this distribution.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
Computes the quantile function of this distribution.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.UniformContinuousDistribution
-
Computes the quantile function of this distribution.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.UniformDiscreteDistribution
-
Computes the quantile function of this distribution.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.WeibullDistribution
-
Computes the quantile function of this distribution.
- inverseLower(double, double, boolean) - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
Compute the inverse cumulative or survival probability using the lower sum.
- inverseProbability(double, double, boolean) - Method in class org.apache.commons.statistics.distribution.AbstractContinuousDistribution
-
Implementation for the inverse cumulative or survival probability.
- inverseProbability(double, double, boolean) - Method in class org.apache.commons.statistics.distribution.AbstractDiscreteDistribution
-
Implementation for the inverse cumulative or survival probability.
- inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.AbstractContinuousDistribution
-
Computes the inverse survival probability function of this distribution.
- inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.AbstractDiscreteDistribution
-
Computes the inverse survival probability function of this distribution.
- inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.CauchyDistribution
-
Computes the inverse survival probability function of this distribution.
- inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.ChiSquaredDistribution
-
Computes the inverse survival probability function of this distribution.
- inverseSurvivalProbability(double) - Method in interface org.apache.commons.statistics.distribution.ContinuousDistribution
-
Computes the inverse survival probability function of this distribution.
- inverseSurvivalProbability(double) - Method in interface org.apache.commons.statistics.distribution.DiscreteDistribution
-
Computes the inverse survival probability function of this distribution.
- inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.ExponentialDistribution
-
Computes the inverse survival probability function of this distribution.
- inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.HalfNormalDistribution
-
Computes the inverse survival probability function of this distribution.
- inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.GeometricDistribution
-
Computes the inverse survival probability function of this distribution.
- inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.GumbelDistribution
-
Computes the inverse survival probability function of this distribution.
- inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
- inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.LaplaceDistribution
-
Computes the inverse survival probability function of this distribution.
- inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.LevyDistribution
-
Computes the inverse survival probability function of this distribution.
- inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.LogisticDistribution
-
Computes the inverse survival probability function of this distribution.
- inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.LogNormalDistribution
-
Computes the inverse survival probability function of this distribution.
- inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.LogUniformDistribution
- inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.NormalDistribution
-
Computes the inverse survival probability function of this distribution.
- inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.ParetoDistribution
-
Computes the inverse survival probability function of this distribution.
- inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.TDistribution
-
Computes the inverse survival probability function of this distribution.
- inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.DelegatedTrapezoidalDistribution
- inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.RegularTrapezoidalDistribution
- inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.TriangularDistribution
-
Computes the inverse survival probability function of this distribution.
- inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
Computes the inverse survival probability function of this distribution.
- inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.UniformContinuousDistribution
-
Computes the inverse survival probability function of this distribution.
- inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.UniformDiscreteDistribution
-
Computes the inverse survival probability function of this distribution.
- inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.WeibullDistribution
-
Computes the inverse survival probability function of this distribution.
- inverseUpper(double, double, boolean) - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
Compute the inverse cumulative or survival probability using the upper sum.
- isBiased() - Method in class org.apache.commons.statistics.descriptive.StatisticsConfiguration
-
Checks if the calculation of the statistic is biased.
- isEmpty() - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest.XYList
-
Checks if the list size is zero.
- isFiniteStrictlyPositive(double) - Static method in class org.apache.commons.statistics.distribution.ArgumentUtils
-
Checks if the value
x
is finite and strictly positive. - isFull() - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest.XYList
-
Checks if the list is the maximum capacity.
- isSupportConnected() - Method in class org.apache.commons.statistics.distribution.AbstractContinuousDistribution
-
Indicates whether the support is connected, i.e.
- isSupported(Statistic) - Method in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
Check if the specified
statistic
is supported. - isSupported(Statistic) - Method in class org.apache.commons.statistics.descriptive.IntStatistics
-
Check if the specified
statistic
is supported. - isSupported(Statistic) - Method in class org.apache.commons.statistics.descriptive.LongStatistics
-
Check if the specified
statistic
is supported. - iterations - Variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Number of iterations .
K
- KolmogorovSmirnovDistribution - Class in org.apache.commons.statistics.inference
-
Computes the complementary probability for the one-sample Kolmogorov-Smirnov distribution.
- KolmogorovSmirnovDistribution() - Constructor for class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution
-
No instances.
- KolmogorovSmirnovDistribution.One - Class in org.apache.commons.statistics.inference
-
Computes the complementary probability
P[D_n^+ >= x]
for the one-sided one-sample Kolmogorov-Smirnov distribution. - KolmogorovSmirnovDistribution.One.ScaledPower - Interface in org.apache.commons.statistics.inference
-
Defines a scaled power function.
- KolmogorovSmirnovDistribution.Two - Class in org.apache.commons.statistics.inference
-
Computes the complementary probability
P[D_n >= x]
, or survival function (SF), for the two-sided one-sample Kolmogorov-Smirnov distribution. - KolmogorovSmirnovTest - Class in org.apache.commons.statistics.inference
-
Implements the Kolmogorov-Smirnov (K-S) test for equality of continuous distributions.
- KolmogorovSmirnovTest(AlternativeHypothesis, PValueMethod, boolean, UniformRandomProvider, int) - Constructor for class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
- KolmogorovSmirnovTest.OneResult - Class in org.apache.commons.statistics.inference
-
Result for the one-sample Kolmogorov-Smirnov test.
- KolmogorovSmirnovTest.TwoResult - Class in org.apache.commons.statistics.inference
-
Result for the two-sample Kolmogorov-Smirnov test.
- ksSum(double) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution
-
Computes
P(sqrt(n) D_n > x)
, the limiting form for the distribution of Kolmogorov's D_n as described in Simard and L’Ecuyer (2011) (Eq. - Kurtosis - Class in org.apache.commons.statistics.descriptive
-
Computes the kurtosis of the available values.
- Kurtosis() - Constructor for class org.apache.commons.statistics.descriptive.Kurtosis
-
Create an instance.
- Kurtosis(SumOfFourthDeviations) - Constructor for class org.apache.commons.statistics.descriptive.Kurtosis
-
Creates an instance with the sum of fourth deviations from the mean.
- KURTOSIS - org.apache.commons.statistics.descriptive.Statistic
-
Kurtosis.
L
- LaplaceDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the Laplace distribution.
- LaplaceDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.LaplaceDistribution
- LARGE_SAMPLE - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
When the largest sample size exceeds this value, 2-sample test AUTO p-value uses an asymptotic distribution to compute the p-value.
- LENGTH_FOUR - Static variable in class org.apache.commons.statistics.descriptive.Kurtosis
-
4, the length limit where the kurtosis is undefined.
- LENGTH_THREE - Static variable in class org.apache.commons.statistics.descriptive.Skewness
-
3, the length limit where the unbiased skewness is undefined.
- LENGTH_TWO - Static variable in class org.apache.commons.statistics.descriptive.Kurtosis
-
2, the length limit where the biased skewness is undefined.
- LENGTH_TWO - Static variable in class org.apache.commons.statistics.descriptive.Skewness
-
2, the length limit where the biased skewness is undefined.
- LENGTH_TWO - Static variable in class org.apache.commons.statistics.descriptive.SumOfCubedDeviations
-
2, the length limit where the sum-of-cubed deviations is zero.
- LESS_THAN - org.apache.commons.statistics.inference.AlternativeHypothesis
-
Represents a left-sided test.
- LevyDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the Lévy distribution.
- LevyDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.LevyDistribution
- LN_LN_2 - Static variable in class org.apache.commons.statistics.distribution.GumbelDistribution
-
ln(ln(2)).
- LN_TWO - Static variable in class org.apache.commons.statistics.distribution.Constants
-
ln(2).
- lo - Variable in class org.apache.commons.statistics.descriptive.Int128
-
low 64-bits.
- lo - Variable in class org.apache.commons.statistics.inference.BracketFinder
-
Lower bound of the bracket.
- lo32() - Method in class org.apache.commons.statistics.descriptive.UInt128
-
Return the low 32-bits as an
int
value. - lo32() - Method in class org.apache.commons.statistics.descriptive.UInt96
-
Return the lower 32-bits as an
int
value. - lo64() - Method in class org.apache.commons.statistics.descriptive.Int128
-
Return the lower 64-bits as a
long
value. - lo64() - Method in class org.apache.commons.statistics.descriptive.UInt128
-
Return the lower 64-bits as a
long
value. - lo64() - Method in class org.apache.commons.statistics.descriptive.UInt192
-
Return the lower 64-bits as a
long
value. - location - Variable in class org.apache.commons.statistics.distribution.CauchyDistribution
-
The location of this distribution.
- LOCK - Static variable in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
An object to use for synchonization when accessing the cache of F.
- LOG_MIN_NORMAL - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
Approximate threshold for ln(MIN_NORMAL).
- LOG_PG_MIN - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
Threshold for Pelz-Good where the 1 - CDF == 1.
- log1mProbabilityOfSuccess - Variable in class org.apache.commons.statistics.distribution.GeometricDistribution
-
log(1 - p)
where p is the probability of success. - log1mProbabilityOfSuccess - Variable in class org.apache.commons.statistics.distribution.PascalDistribution
-
The value of
log(1-p)
, wherep
is the probability of success, stored for faster computation. - log2(int) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.One
-
Returns
floor(log2(n))
. - log2beta - Variable in class org.apache.commons.statistics.distribution.LaplaceDistribution
-
log(2 * beta).
- logA - Variable in class org.apache.commons.statistics.distribution.LogUniformDistribution
-
log(a).
- logB - Variable in class org.apache.commons.statistics.distribution.LogUniformDistribution
-
log(b).
- logBeta - Variable in class org.apache.commons.statistics.distribution.BetaDistribution
-
Normalizing factor used in log density computations.
- logBetaNhalfMhalf - Variable in class org.apache.commons.statistics.distribution.FDistribution
-
LogBeta(n/2, n/2) with n = numerator DF.
- logBinomialProbability(int, int, double, double) - Static method in class org.apache.commons.statistics.distribution.SaddlePointExpansionUtils
-
Compute the logarithm of the PMF for a binomial distribution using the saddle point expansion.
- logBmLogA - Variable in class org.apache.commons.statistics.distribution.LogUniformDistribution
-
log(b) - log(a).
- logCdfDelta - Variable in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
log(cdfDelta).
- logDensity(double) - Method in class org.apache.commons.statistics.distribution.BetaDistribution
-
Returns the natural logarithm of the probability density function (PDF) of this distribution evaluated at the specified point
x
. - logDensity(double) - Method in class org.apache.commons.statistics.distribution.ChiSquaredDistribution
-
Returns the natural logarithm of the probability density function (PDF) of this distribution evaluated at the specified point
x
. - logDensity(double) - Method in interface org.apache.commons.statistics.distribution.ContinuousDistribution
-
Returns the natural logarithm of the probability density function (PDF) of this distribution evaluated at the specified point
x
. - logDensity(double) - Method in class org.apache.commons.statistics.distribution.ExponentialDistribution
-
Returns the natural logarithm of the probability density function (PDF) of this distribution evaluated at the specified point
x
. - logDensity(double) - Method in class org.apache.commons.statistics.distribution.FDistribution
-
Returns the natural logarithm of the probability density function (PDF) of this distribution evaluated at the specified point
x
. - logDensity(double) - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.HalfNormalDistribution
- logDensity(double) - Method in class org.apache.commons.statistics.distribution.GammaDistribution
-
Returns the natural logarithm of the probability density function (PDF) of this distribution evaluated at the specified point
x
. - logDensity(double) - Method in class org.apache.commons.statistics.distribution.GumbelDistribution
-
Returns the natural logarithm of the probability density function (PDF) of this distribution evaluated at the specified point
x
. - logDensity(double) - Method in class org.apache.commons.statistics.distribution.LaplaceDistribution
-
Returns the natural logarithm of the probability density function (PDF) of this distribution evaluated at the specified point
x
. - logDensity(double) - Method in class org.apache.commons.statistics.distribution.LevyDistribution
-
Returns the natural logarithm of the probability density function (PDF) of this distribution evaluated at the specified point
x
. - logDensity(double) - Method in class org.apache.commons.statistics.distribution.LogisticDistribution
-
Returns the natural logarithm of the probability density function (PDF) of this distribution evaluated at the specified point
x
. - logDensity(double) - Method in class org.apache.commons.statistics.distribution.LogNormalDistribution
-
Returns the natural logarithm of the probability density function (PDF) of this distribution evaluated at the specified point
x
. - logDensity(double) - Method in class org.apache.commons.statistics.distribution.LogUniformDistribution
-
Returns the natural logarithm of the probability density function (PDF) of this distribution evaluated at the specified point
x
. - logDensity(double) - Method in class org.apache.commons.statistics.distribution.NakagamiDistribution
-
Returns the natural logarithm of the probability density function (PDF) of this distribution evaluated at the specified point
x
. - logDensity(double) - Method in class org.apache.commons.statistics.distribution.NormalDistribution
-
Returns the natural logarithm of the probability density function (PDF) of this distribution evaluated at the specified point
x
. - logDensity(double) - Method in class org.apache.commons.statistics.distribution.ParetoDistribution
-
Returns the natural logarithm of the probability density function (PDF) of this distribution evaluated at the specified point
x
. - logDensity(double) - Method in class org.apache.commons.statistics.distribution.TDistribution.NormalTDistribution
- logDensity(double) - Method in class org.apache.commons.statistics.distribution.TDistribution.StudentsTDistribution
- logDensity(double) - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.DelegatedTrapezoidalDistribution
- logDensity(double) - Method in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
Returns the natural logarithm of the probability density function (PDF) of this distribution evaluated at the specified point
x
. - logDensity(double) - Method in class org.apache.commons.statistics.distribution.UniformContinuousDistribution
-
Returns the natural logarithm of the probability density function (PDF) of this distribution evaluated at the specified point
x
. - logDensity(double) - Method in class org.apache.commons.statistics.distribution.WeibullDistribution
-
Returns the natural logarithm of the probability density function (PDF) of this distribution evaluated at the specified point
x
. - logDensityNormalisation - Variable in class org.apache.commons.statistics.distribution.TDistribution.StudentsTDistribution
-
Log density normalisation term, 0.5 * log(v) + log(beta(1/2, v/2)), where v = degrees of freedom.
- logDensityPrefactor - Variable in class org.apache.commons.statistics.distribution.NakagamiDistribution
-
Log density prefactor.
- LogisticDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the logistic distribution.
- LogisticDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.LogisticDistribution
- logLogBmLogA - Variable in class org.apache.commons.statistics.distribution.LogUniformDistribution
-
log(log(b) - log(a)).
- logMean - Variable in class org.apache.commons.statistics.distribution.ExponentialDistribution
-
The logarithm of the mean, stored to reduce computing time.
- LogNormalDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the log-normal distribution.
- LogNormalDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.LogNormalDistribution
- logNthHarmonic - Variable in class org.apache.commons.statistics.distribution.ZipfDistribution
-
Cached value of the log of the nth generalized harmonic.
- logpdf - Variable in class org.apache.commons.statistics.distribution.ParetoDistribution
-
Implementation of log PDF(x).
- logPdf - Variable in class org.apache.commons.statistics.distribution.UniformContinuousDistribution
-
Cache of the log density.
- logPmf - Variable in class org.apache.commons.statistics.distribution.UniformDiscreteDistribution
-
Cache of the log probability.
- logProbability(int) - Method in class org.apache.commons.statistics.distribution.BinomialDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnslog(P(X = x))
, wherelog
is the natural logarithm. - logProbability(int) - Method in interface org.apache.commons.statistics.distribution.DiscreteDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnslog(P(X = x))
, wherelog
is the natural logarithm. - logProbability(int) - Method in class org.apache.commons.statistics.distribution.GeometricDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnslog(P(X = x))
, wherelog
is the natural logarithm. - logProbability(int) - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnslog(P(X = x))
, wherelog
is the natural logarithm. - logProbability(int) - Method in class org.apache.commons.statistics.distribution.PascalDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnslog(P(X = x))
, wherelog
is the natural logarithm. - logProbability(int) - Method in class org.apache.commons.statistics.distribution.PoissonDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnslog(P(X = x))
, wherelog
is the natural logarithm. - logProbability(int) - Method in class org.apache.commons.statistics.distribution.UniformDiscreteDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnslog(P(X = x))
, wherelog
is the natural logarithm. - logProbability(int) - Method in class org.apache.commons.statistics.distribution.ZipfDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnslog(P(X = x))
, wherelog
is the natural logarithm. - logProbabilityOfSuccess - Variable in class org.apache.commons.statistics.distribution.GeometricDistribution
-
log(p)
where p is the probability of success. - logProbabilityOfSuccessByNumOfSuccesses - Variable in class org.apache.commons.statistics.distribution.PascalDistribution
-
The value of
log(p) * n
, wherep
is the probability of success andn
is the number of successes, stored for faster computation. - logScale - Variable in class org.apache.commons.statistics.distribution.LogisticDistribution
-
Logarithm of "scale".
- logShapeOverScale - Variable in class org.apache.commons.statistics.distribution.WeibullDistribution
-
log(shape / scale).
- logSigmaPlusHalfLog2Pi - Variable in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.HalfNormalDistribution
-
The value of
log(sigma) + 0.5 * log(2*PI)
stored for faster computation. - logSigmaPlusHalfLog2Pi - Variable in class org.apache.commons.statistics.distribution.LogNormalDistribution
-
The value of
log(sigma) + 0.5 * log(2*PI)
stored for faster computation. - logStandardDeviationPlusHalfLog2Pi - Variable in class org.apache.commons.statistics.distribution.NormalDistribution
-
The value of
log(sd) + 0.5*log(2*pi)
stored for faster computation. - LogUniformDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the log-uniform distribution.
- LogUniformDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.LogUniformDistribution
- LONG_NOOP - Static variable in class org.apache.commons.statistics.descriptive.Statistics
-
A no-operation long consumer.
- LongMax - Class in org.apache.commons.statistics.descriptive
-
Returns the maximum of the available values.
- LongMax() - Constructor for class org.apache.commons.statistics.descriptive.LongMax
-
Create an instance.
- LongMean - Class in org.apache.commons.statistics.descriptive
-
Computes the arithmetic mean of the available values.
- LongMean() - Constructor for class org.apache.commons.statistics.descriptive.LongMean
-
Create an instance.
- LongMean(Int128, int) - Constructor for class org.apache.commons.statistics.descriptive.LongMean
-
Create an instance.
- LongMin - Class in org.apache.commons.statistics.descriptive
-
Returns the minimum of the available values.
- LongMin() - Constructor for class org.apache.commons.statistics.descriptive.LongMin
-
Create an instance.
- LongStandardDeviation - Class in org.apache.commons.statistics.descriptive
-
Computes the standard deviation of the available values.
- LongStandardDeviation() - Constructor for class org.apache.commons.statistics.descriptive.LongStandardDeviation
-
Create an instance.
- LongStandardDeviation(UInt192, Int128, int) - Constructor for class org.apache.commons.statistics.descriptive.LongStandardDeviation
-
Create an instance.
- LongStatistic - Interface in org.apache.commons.statistics.descriptive
-
Represents a state object for computing a statistic over
long
valued input(s). - LongStatisticResult - Interface in org.apache.commons.statistics.descriptive
-
Represents the
long
result of a statistic computed over a set of values. - LongStatistics - Class in org.apache.commons.statistics.descriptive
-
Statistics for
long
values. - LongStatistics(long, LongMin, LongMax, FirstMoment, LongSum, Product, LongSumOfSquares, SumOfLogs, StatisticsConfiguration) - Constructor for class org.apache.commons.statistics.descriptive.LongStatistics
-
Create an instance.
- LongStatistics.Builder - Class in org.apache.commons.statistics.descriptive
-
A builder for
LongStatistics
. - LongSum - Class in org.apache.commons.statistics.descriptive
-
Returns the sum of the available values.
- LongSum() - Constructor for class org.apache.commons.statistics.descriptive.LongSum
-
Create an instance.
- LongSum(Int128) - Constructor for class org.apache.commons.statistics.descriptive.LongSum
-
Create an instance.
- LongSumOfSquares - Class in org.apache.commons.statistics.descriptive
-
Returns the sum of the squares of the available values.
- LongSumOfSquares() - Constructor for class org.apache.commons.statistics.descriptive.LongSumOfSquares
-
Create an instance.
- LongSumOfSquares(UInt192) - Constructor for class org.apache.commons.statistics.descriptive.LongSumOfSquares
-
Create an instance.
- LongVariance - Class in org.apache.commons.statistics.descriptive
-
Computes the variance of the available values.
- LongVariance() - Constructor for class org.apache.commons.statistics.descriptive.LongVariance
-
Create an instance.
- LongVariance(UInt192, Int128, int) - Constructor for class org.apache.commons.statistics.descriptive.LongVariance
-
Create an instance.
- lower - Variable in class org.apache.commons.statistics.distribution.LogUniformDistribution
-
Lower bound (a) of this distribution (inclusive).
- lower - Variable in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
Lower bound of this distribution.
- lower - Variable in class org.apache.commons.statistics.distribution.UniformContinuousDistribution
-
Lower bound of this distribution (inclusive).
- lower - Variable in class org.apache.commons.statistics.distribution.UniformDiscreteDistribution
-
Lower bound (inclusive) of this distribution.
- LOWER_BOUND - Static variable in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Lower bound for the enumerated interval.
- lowerBound - Variable in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
The lower bound of the support (inclusive).
- lowerBound - Variable in class org.apache.commons.statistics.inference.Hypergeom
-
The lower bound of the support (inclusive).
M
- m - Variable in class org.apache.commons.statistics.inference.Hypergeom
-
Cached midpoint, m, of the CDF/SF.
- m1 - Variable in class org.apache.commons.statistics.descriptive.FirstMoment
-
First moment of values that have been added.
- m1 - Variable in class org.apache.commons.statistics.inference.Hypergeom
-
Lower mode.
- m2 - Variable in class org.apache.commons.statistics.inference.Hypergeom
-
Upper mode.
- MannWhitneyUTest - Class in org.apache.commons.statistics.inference
-
Implements the Mann-Whitney U test (also called Wilcoxon rank-sum test).
- MannWhitneyUTest(AlternativeHypothesis, PValueMethod, boolean, double) - Constructor for class org.apache.commons.statistics.inference.MannWhitneyUTest
- MannWhitneyUTest.Result - Class in org.apache.commons.statistics.inference
-
Result for the Mann-Whitney U test.
- MASK32 - Static variable in class org.apache.commons.statistics.descriptive.Int128
-
Mask for the lower 32-bits of a long.
- MASK32 - Static variable in class org.apache.commons.statistics.descriptive.IntMath
-
Mask for the lower 32-bits of a long.
- MASK32 - Static variable in class org.apache.commons.statistics.descriptive.UInt128
-
Mask for the lower 32-bits of a long.
- MASK32 - Static variable in class org.apache.commons.statistics.descriptive.UInt192
-
Mask for the lower 32-bits of a long.
- MASK32 - Static variable in class org.apache.commons.statistics.descriptive.UInt96
-
Mask for the lower 32-bits of a long.
- MASK52 - Static variable in class org.apache.commons.statistics.descriptive.IntMath
-
Mask for the lower 52-bits of a long.
- max - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
-
The
Max
constructor. - max - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
The
Max
implementation. - max - Variable in class org.apache.commons.statistics.descriptive.IntStatistics.Builder
-
The
IntMax
constructor. - max - Variable in class org.apache.commons.statistics.descriptive.IntStatistics
-
The
IntMax
implementation. - max - Variable in class org.apache.commons.statistics.descriptive.LongStatistics.Builder
-
The
LongMax
constructor. - max - Variable in class org.apache.commons.statistics.descriptive.LongStatistics
-
The
LongMax
implementation. - max - Variable in class org.apache.commons.statistics.inference.UnconditionedExactTest.Candidates
-
The maximum size of array to allocate.
- max - Variable in class org.apache.commons.statistics.inference.UnconditionedExactTest.XYList
-
The maximum size of array to allocate.
- max - Variable in class org.apache.commons.statistics.ranking.NaturalRanking.IntList
-
The maximum size of array to allocate.
- Max - Class in org.apache.commons.statistics.descriptive
-
Returns the maximum of the available values.
- Max() - Constructor for class org.apache.commons.statistics.descriptive.Max
-
Create an instance.
- MAX - org.apache.commons.statistics.descriptive.Statistic
-
Maximum.
- MAX_ARRAY_SIZE - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Maximum length of an array.
- MAX_CANDIDATES - Static variable in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Maximum number of candidate to optimize.
- MAX_FACTORIAL - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
Maximum finite factorial.
- MAX_FACTORIAL - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Maximum finite factorial.
- MAX_LCM_TWO_SAMPLE_EXACT_P - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
The maximum least common multiple (lcm) to attempt the exact p-value computation.
- MAX_MEAN - Static variable in class org.apache.commons.statistics.distribution.PoissonDistribution
-
Upper bound on the mean to use the PoissonSampler.
- MAX_TABLES - Static variable in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
The maximum number of tables.
- MAX_X - Static variable in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
The max allowed value for x where (x*x) will not overflow.
- maxEvaluations - Variable in class org.apache.commons.statistics.inference.BracketFinder
-
Number of allowed function evaluations.
- MAXIMAL - org.apache.commons.statistics.ranking.NaNStrategy
-
NaNs are considered maximal in the ordering, equivalent to (that is, tied with) positive infinity.
- maximum - Variable in class org.apache.commons.statistics.descriptive.IntMax
-
Current maximum.
- maximum - Variable in class org.apache.commons.statistics.descriptive.LongMax
-
Current maximum.
- maximum - Variable in class org.apache.commons.statistics.descriptive.Max
-
Current maximum.
- MAXIMUM - org.apache.commons.statistics.ranking.TiesStrategy
-
Tied values are assigned the maximum applicable rank, or the rank of the last occurrence.
- mean - Variable in class org.apache.commons.statistics.distribution.BetaDistribution
-
Cached value for inverse probability function.
- mean - Variable in class org.apache.commons.statistics.distribution.ExponentialDistribution
-
The mean of this distribution.
- mean - Variable in class org.apache.commons.statistics.distribution.FDistribution
-
Cached value for inverse probability function.
- mean - Variable in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.RegularFoldedNormalDistribution
-
Cached value for inverse probability function.
- mean - Variable in class org.apache.commons.statistics.distribution.GammaDistribution
-
Cached value for inverse probability function.
- mean - Variable in class org.apache.commons.statistics.distribution.NakagamiDistribution
-
Cached value for inverse probability function.
- mean - Variable in class org.apache.commons.statistics.distribution.NormalDistribution
-
Mean of this distribution.
- mean - Variable in class org.apache.commons.statistics.distribution.PoissonDistribution
-
Mean of the distribution.
- mean - Variable in class org.apache.commons.statistics.distribution.TDistribution.StudentsTDistribution
-
Cached value for inverse probability function.
- mean(double, double) - Static method in class org.apache.commons.statistics.descriptive.Interpolation
-
Compute the arithmetic mean of the two values taking care to avoid overflow.
- mean(int, int) - Static method in class org.apache.commons.statistics.descriptive.Interpolation
-
Compute the arithmetic mean of the two values.
- mean(Collection<double[]>) - Static method in class org.apache.commons.statistics.inference.StatisticUtils
-
Returns the arithmetic mean of the entries in the input arrays, or
NaN
if the combined length of the arrays is zero. - Mean - Class in org.apache.commons.statistics.descriptive
-
Computes the arithmetic mean of the available values.
- Mean() - Constructor for class org.apache.commons.statistics.descriptive.Mean
-
Create an instance.
- Mean(FirstMoment) - Constructor for class org.apache.commons.statistics.descriptive.Mean
-
Creates an instance with a moment.
- MEAN - org.apache.commons.statistics.descriptive.Statistic
-
Mean, or average.
- meanDifference(double[], double[]) - Static method in class org.apache.commons.statistics.inference.StatisticUtils
-
Returns the mean of the (signed) differences between corresponding elements of the input arrays.
- median - Variable in class org.apache.commons.statistics.distribution.AbstractContinuousDistribution
-
Cached value of the median.
- median - Variable in class org.apache.commons.statistics.distribution.AbstractDiscreteDistribution
-
Cached value of the median.
- Median - Class in org.apache.commons.statistics.descriptive
-
Returns the median of the available values.
- Median(boolean, NaNPolicy) - Constructor for class org.apache.commons.statistics.descriptive.Median
- method - Variable in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Method to identify more extreme tables.
- Method() - Constructor for enum org.apache.commons.statistics.inference.UnconditionedExactTest.Method
- mid - Variable in class org.apache.commons.statistics.inference.BracketFinder
-
Point inside the bracket.
- mid32() - Method in class org.apache.commons.statistics.descriptive.UInt128
-
Return the middle 32-bits as an
int
value. - mid64() - Method in class org.apache.commons.statistics.descriptive.UInt192
-
Return the middle 64-bits as a
long
value. - midCDF - Variable in class org.apache.commons.statistics.inference.Hypergeom
-
Cached CDF of the midpoint.
- midpoint - Variable in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
Cached midpoint of the CDF/SF.
- min - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
-
The
Min
constructor. - min - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
The
Min
implementation. - min - Variable in class org.apache.commons.statistics.descriptive.IntStatistics.Builder
-
The
IntMin
constructor. - min - Variable in class org.apache.commons.statistics.descriptive.IntStatistics
-
The
IntMin
implementation. - min - Variable in class org.apache.commons.statistics.descriptive.LongStatistics.Builder
-
The
LongMin
constructor. - min - Variable in class org.apache.commons.statistics.descriptive.LongStatistics
-
The
LongMin
implementation. - min - Variable in class org.apache.commons.statistics.inference.UnconditionedExactTest.Candidates
-
Current minimum.
- Min - Class in org.apache.commons.statistics.descriptive
-
Returns the minimum of the available values.
- Min() - Constructor for class org.apache.commons.statistics.descriptive.Min
-
Create an instance.
- MIN - org.apache.commons.statistics.descriptive.Statistic
-
Minimum.
- MIN_DENOMINATOR_DF_FOR_MEAN - Static variable in class org.apache.commons.statistics.distribution.FDistribution
-
The minimum degrees of freedom for the denominator when computing the mean.
- MIN_DENOMINATOR_DF_FOR_VARIANCE - Static variable in class org.apache.commons.statistics.distribution.FDistribution
-
The minimum degrees of freedom for the denominator when computing the variance.
- MIN_P - Static variable in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
The min allowed probability range of the parent normal distribution.
- MIN_RELATIVE_TOLERANCE - Static variable in class org.apache.commons.statistics.inference.BrentOptimizer
-
Minimum relative tolerance.
- MIN_SHAPE_FOR_VARIANCE - Static variable in class org.apache.commons.statistics.distribution.ParetoDistribution
-
The minimum value for the shape parameter when computing when computing the variance.
- MINIMA_EPS - Static variable in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Relative distance of candidate minima from the lowest candidate.
- MINIMAL - org.apache.commons.statistics.ranking.NaNStrategy
-
NaNs are considered minimal in the ordering, equivalent to (that is, tied with) negative infinity.
- minimum - Variable in class org.apache.commons.statistics.descriptive.IntMin
-
Current minimum.
- minimum - Variable in class org.apache.commons.statistics.descriptive.LongMin
-
Current minimum.
- minimum - Variable in class org.apache.commons.statistics.descriptive.Min
-
Current minimum.
- MINIMUM - org.apache.commons.statistics.ranking.TiesStrategy
-
Tied values are assigned the minimum applicable rank, or the rank of the first occurrence.
- minusLogGammaShapeMinusLogScale - Variable in class org.apache.commons.statistics.distribution.GammaDistribution
-
Precomputed term for the log density:
-log(gamma(shape)) - log(scale)
. - moment - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
-
The moment constructor.
- moment - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
The moment implementation.
- moment - Variable in class org.apache.commons.statistics.descriptive.IntStatistics.Builder
-
The moment constructor.
- moment - Variable in class org.apache.commons.statistics.descriptive.IntStatistics
-
The moment implementation.
- moment - Variable in class org.apache.commons.statistics.descriptive.LongStatistics.Builder
-
The moment constructor.
- moment - Variable in class org.apache.commons.statistics.descriptive.LongStatistics
-
The moment implementation.
- moment1(double, double) - Static method in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
Compute the first moment (mean) of the truncated standard normal distribution.
- moment2(double, double) - Static method in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
Compute the second moment of the truncated standard normal distribution.
- momentOrder - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
-
The order of the moment.
- momentOrder - Variable in class org.apache.commons.statistics.descriptive.IntStatistics.Builder
-
The order of the moment.
- momentOrder - Variable in class org.apache.commons.statistics.descriptive.LongStatistics.Builder
-
The order of the moment.
- msbg - Variable in class org.apache.commons.statistics.inference.OneWayAnova.Result
-
Mean square between groups.
- mswg - Variable in class org.apache.commons.statistics.inference.OneWayAnova.Result
-
Mean square within groups.
- MTW_SCALE_THRESHOLD - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
The scaling threshold in the MTW algorithm.
- MTW_UP_SCALE - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
The up-scaling factor in the MTW algorithm.
- MTW_UP_SCALE_POWER - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
The power-of-2 of the up-scaling factor in the MTW algorithm, n if the up-scale factor is 2^n.
- mu - Variable in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.RegularFoldedNormalDistribution
-
The location.
- mu - Variable in class org.apache.commons.statistics.distribution.GumbelDistribution
-
Location parameter.
- mu - Variable in class org.apache.commons.statistics.distribution.LaplaceDistribution
-
The location parameter.
- mu - Variable in class org.apache.commons.statistics.distribution.LevyDistribution
-
Location parameter.
- mu - Variable in class org.apache.commons.statistics.distribution.LogisticDistribution
-
Location parameter.
- mu - Variable in class org.apache.commons.statistics.distribution.LogNormalDistribution
-
The mu parameter of this distribution.
- mu - Variable in class org.apache.commons.statistics.distribution.NakagamiDistribution
-
The shape parameter.
- mu - Variable in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
Expected location shift.
- mu - Variable in class org.apache.commons.statistics.inference.TTest
-
The true value of the mean (or difference in means for a two sample test).
- mu - Variable in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Expected location shift.
- multiply(double[], int, double[], int, double[], double[]) - Static method in class org.apache.commons.statistics.inference.SquareMatrixSupport.ArrayRealSquareMatrix
-
Returns the result of postmultiplying
a
byb
. - mvp1Over2 - Variable in class org.apache.commons.statistics.distribution.TDistribution.StudentsTDistribution
-
-(v + 1) / 2, where v = degrees of freedom.
N
- n - Variable in class org.apache.commons.statistics.descriptive.FirstMoment
-
Count of values that have been added.
- n - Variable in class org.apache.commons.statistics.descriptive.GeometricMean
-
Count of values that have been added.
- n - Variable in class org.apache.commons.statistics.descriptive.IntMean
-
Count of values that have been added.
- n - Variable in class org.apache.commons.statistics.descriptive.IntStandardDeviation
-
Count of values that have been added.
- n - Variable in class org.apache.commons.statistics.descriptive.IntVariance
-
Count of values that have been added.
- n - Variable in class org.apache.commons.statistics.descriptive.LongMean
-
Count of values that have been added.
- n - Variable in class org.apache.commons.statistics.descriptive.LongStandardDeviation
-
Count of values that have been added.
- n - Variable in class org.apache.commons.statistics.descriptive.LongVariance
-
Count of values that have been added.
- N_100000 - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
100000, n threshold for large n Durbin matrix sf computation.
- N140 - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
140, n threshold for small n for the sf computation.
- NakagamiDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the Nakagami distribution.
- NakagamiDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.NakagamiDistribution
- nanPolicy - Variable in class org.apache.commons.statistics.descriptive.Median
-
NaN policy for floating point data.
- nanPolicy - Variable in class org.apache.commons.statistics.descriptive.Quantile
-
NaN policy for floating point data.
- NaNPolicy - Enum in org.apache.commons.statistics.descriptive
-
Defines the policy for
NaN
values found in data. - NaNPolicy() - Constructor for enum org.apache.commons.statistics.descriptive.NaNPolicy
- nanStrategy - Variable in class org.apache.commons.statistics.ranking.NaturalRanking
-
NaN strategy.
- NaNStrategy - Enum in org.apache.commons.statistics.ranking
-
Strategies for handling
NaN
values in rank transformations. - NaNStrategy() - Constructor for enum org.apache.commons.statistics.ranking.NaNStrategy
- nanTransformer - Variable in class org.apache.commons.statistics.descriptive.Median
-
Transformer for NaN data.
- nanTransformer - Variable in class org.apache.commons.statistics.descriptive.Quantile
-
Transformer for NaN data.
- NaNTransformer - Interface in org.apache.commons.statistics.descriptive
-
Defines a transformer for
NaN
values in arrays. - NaNTransformers - Class in org.apache.commons.statistics.descriptive
-
Support for creating
NaNTransformer
implementations. - NaNTransformers() - Constructor for class org.apache.commons.statistics.descriptive.NaNTransformers
-
No instances.
- NaNTransformers.ErrorNaNTransformer - Class in org.apache.commons.statistics.descriptive
-
A transformer that errors on
NaN
. - NaNTransformers.ExcludeNaNTransformer - Class in org.apache.commons.statistics.descriptive
-
A transformer that moves
NaN
to the upper end of the array. - NaNTransformers.IncludeNaNTransformer - Class in org.apache.commons.statistics.descriptive
-
A NaN transformer that optionally copies the data.
- NaturalRanking - Class in org.apache.commons.statistics.ranking
-
Ranking based on the natural ordering on floating-point values.
- NaturalRanking() - Constructor for class org.apache.commons.statistics.ranking.NaturalRanking
-
Creates an instance with
FAILED
andTiesStrategy.AVERAGE
. - NaturalRanking(IntUnaryOperator) - Constructor for class org.apache.commons.statistics.ranking.NaturalRanking
-
Creates an instance with
FAILED
,TiesStrategy.RANDOM
and the given the source of random index data. - NaturalRanking(NaNStrategy) - Constructor for class org.apache.commons.statistics.ranking.NaturalRanking
-
Creates an instance with the specified @
nanStrategy
andTiesStrategy.AVERAGE
. - NaturalRanking(NaNStrategy, IntUnaryOperator) - Constructor for class org.apache.commons.statistics.ranking.NaturalRanking
-
Creates an instance with the specified @
nanStrategy
,TiesStrategy.RANDOM
and the given the source of random index data. - NaturalRanking(NaNStrategy, TiesStrategy) - Constructor for class org.apache.commons.statistics.ranking.NaturalRanking
-
Creates an instance with the specified @
nanStrategy
and the specified @tiesStrategy
. - NaturalRanking(NaNStrategy, TiesStrategy, IntUnaryOperator) - Constructor for class org.apache.commons.statistics.ranking.NaturalRanking
- NaturalRanking(TiesStrategy) - Constructor for class org.apache.commons.statistics.ranking.NaturalRanking
-
Creates an instance with
FAILED
and the specified @tiesStrategy
. - NaturalRanking.DataPosition - Class in org.apache.commons.statistics.ranking
-
Represents the position of a
double
value in a data array. - NaturalRanking.IntList - Class in org.apache.commons.statistics.ranking
-
An expandable list of int values.
- nDev - Variable in class org.apache.commons.statistics.descriptive.FirstMoment
-
Half the deviation of most recently added value from the previous first moment, normalized by current sample size.
- NEGATIVE - Static variable in exception org.apache.commons.statistics.distribution.DistributionException
-
Error message for "negative" condition when
x < 0
. - NEGATIVE - Static variable in exception org.apache.commons.statistics.inference.InferenceException
-
Error message for "negative" condition when "
x < 0
". - nHalfLogNmHalfLogM - Variable in class org.apache.commons.statistics.distribution.FDistribution
-
n/2 * log(n) + m/2 * log(m) with n = numerator DF and m = denominator DF.
- nO - Variable in class org.apache.commons.statistics.inference.OneWayAnova.Result
-
nO value used to partition the variance.
- NO_CONFIGURED_STATISTICS - Static variable in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
Error message for non configured statistics.
- NO_CONFIGURED_STATISTICS - Static variable in class org.apache.commons.statistics.descriptive.IntStatistics
-
Error message for non configured statistics.
- NO_CONFIGURED_STATISTICS - Static variable in class org.apache.commons.statistics.descriptive.LongStatistics
-
Error message for non configured statistics.
- NO_DATA - Static variable in exception org.apache.commons.statistics.inference.InferenceException
-
Error message for "no data" condition.
- NO_MEDIAN - Static variable in class org.apache.commons.statistics.distribution.AbstractDiscreteDistribution
-
Marker value for no median.
- NO_PROBABILITIES_SPECIFIED - Static variable in class org.apache.commons.statistics.descriptive.Quantile
-
Message when no probabilities are provided for the varargs method.
- NO_VALUES - Static variable in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
-
An empty double array.
- NO_VALUES - Static variable in class org.apache.commons.statistics.descriptive.IntStatistics.Builder
-
An empty double array.
- NO_VALUES - Static variable in class org.apache.commons.statistics.descriptive.LongStatistics.Builder
-
An empty double array.
- NON_STRICT - org.apache.commons.statistics.inference.Inequality
-
Represents a non-strict inequality (numbers may be equal).
- nonCentralMoment(int, double, double) - Static method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.RegularTrapezoidalDistribution
-
Compute the
k
-th non-central moment of the standardized trapezoidal distribution. - nonFiniteValue - Variable in class org.apache.commons.statistics.descriptive.FirstMoment
-
Running sum of values seen so far.
- NormalDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the normal (Gaussian) distribution.
- NormalDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.NormalDistribution
- NormalTDistribution(double) - Constructor for class org.apache.commons.statistics.distribution.TDistribution.NormalTDistribution
- NOT_RECTANGULAR - Static variable in exception org.apache.commons.statistics.inference.InferenceException
-
Error message for "non-rectangular matrix" when "some row lengths x != others y".
- NOT_STRICTLY_POSITIVE - Static variable in exception org.apache.commons.statistics.distribution.DistributionException
-
Error message for "not strictly positive" condition when
x <= 0
. - NOT_STRICTLY_POSITIVE - Static variable in exception org.apache.commons.statistics.inference.InferenceException
-
Error message for "not strictly positive" condition when "
x <= 0
". - NOT_STRICTLY_POSITIVE_FINITE - Static variable in exception org.apache.commons.statistics.distribution.DistributionException
-
Error message for "not strictly positive finite" condition when
x <= 0 || x == inf
. - nthHarmonic - Variable in class org.apache.commons.statistics.distribution.ZipfDistribution
-
Cached value of the nth generalized harmonic.
- NULL_NAN_STRATEGY - Static variable in class org.apache.commons.statistics.ranking.NaturalRanking
-
Message for a null user-supplied
NaNStrategy
. - NULL_RANDOM_SOURCE - Static variable in class org.apache.commons.statistics.ranking.NaturalRanking
-
Message for a null user-supplied source of randomness.
- NULL_TIES_STRATEGY - Static variable in class org.apache.commons.statistics.ranking.NaturalRanking
-
Message for a null user-supplied
TiesStrategy
. - numberOfElements - Variable in class org.apache.commons.statistics.distribution.ZipfDistribution
-
Number of elements.
- numberOfSuccesses - Variable in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
The number of successes in the population.
- numberOfSuccesses - Variable in class org.apache.commons.statistics.distribution.PascalDistribution
-
The number of successes.
- numberOfTrials - Variable in class org.apache.commons.statistics.distribution.BinomialDistribution
-
The number of trials.
- numeratorDegreesOfFreedom - Variable in class org.apache.commons.statistics.distribution.FDistribution
-
The numerator degrees of freedom.
- NX32_1_4 - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
1.4, nx^(3/2) threshold for large n Durbin matrix sf computation.
- NXX_0_754693 - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
0.754693, nxx threshold for small n Durbin matrix sf computation.
- NXX_2_2 - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
2.2, nxx threshold for large n Miller approximation sf computation.
- NXX_4 - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
4, nxx threshold for small n Pomeranz sf computation.
O
- of(double) - Static method in class org.apache.commons.statistics.distribution.ChiSquaredDistribution
-
Creates a chi-squared distribution.
- of(double) - Static method in class org.apache.commons.statistics.distribution.ExponentialDistribution
-
Creates an exponential distribution.
- of(double) - Static method in class org.apache.commons.statistics.distribution.GeometricDistribution
-
Creates a geometric distribution.
- of(double) - Static method in class org.apache.commons.statistics.distribution.PoissonDistribution
-
Creates a Poisson distribution.
- of(double) - Static method in class org.apache.commons.statistics.distribution.TDistribution
-
Creates a Student's t-distribution.
- of(double...) - Static method in class org.apache.commons.statistics.descriptive.FirstMoment
-
Returns an instance populated using the input
values
. - of(double...) - Static method in class org.apache.commons.statistics.descriptive.GeometricMean
-
Returns an instance populated using the input
values
. - of(double...) - Static method in class org.apache.commons.statistics.descriptive.Kurtosis
-
Returns an instance populated using the input
values
. - of(double...) - Static method in class org.apache.commons.statistics.descriptive.Max
-
Returns an instance populated using the input
values
. - of(double...) - Static method in class org.apache.commons.statistics.descriptive.Mean
-
Returns an instance populated using the input
values
. - of(double...) - Static method in class org.apache.commons.statistics.descriptive.Min
-
Returns an instance populated using the input
values
. - of(double...) - Static method in class org.apache.commons.statistics.descriptive.Product
-
Returns an instance populated using the input
values
. - of(double...) - Static method in class org.apache.commons.statistics.descriptive.Skewness
-
Returns an instance populated using the input
values
. - of(double...) - Static method in class org.apache.commons.statistics.descriptive.StandardDeviation
-
Returns an instance populated using the input
values
. - of(double...) - Static method in class org.apache.commons.statistics.descriptive.Sum
-
Returns an instance populated using the input
values
. - of(double...) - Static method in class org.apache.commons.statistics.descriptive.SumOfCubedDeviations
-
Returns an instance populated using the input
values
. - of(double...) - Static method in class org.apache.commons.statistics.descriptive.SumOfFourthDeviations
-
Returns an instance populated using the input
values
. - of(double...) - Static method in class org.apache.commons.statistics.descriptive.SumOfLogs
-
Returns an instance populated using the input
values
. - of(double...) - Static method in class org.apache.commons.statistics.descriptive.SumOfSquaredDeviations
-
Returns an instance populated using the input
values
. - of(double...) - Static method in class org.apache.commons.statistics.descriptive.SumOfSquares
-
Returns an instance populated using the input
values
. - of(double...) - Static method in class org.apache.commons.statistics.descriptive.Variance
-
Returns an instance populated using the input
values
. - of(double, double) - Static method in class org.apache.commons.statistics.distribution.BetaDistribution
-
Creates a beta distribution.
- of(double, double) - Static method in class org.apache.commons.statistics.distribution.CauchyDistribution
-
Creates a Cauchy distribution.
- of(double, double) - Static method in class org.apache.commons.statistics.distribution.FDistribution
-
Creates an F-distribution.
- of(double, double) - Static method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution
-
Creates a folded normal distribution.
- of(double, double) - Static method in class org.apache.commons.statistics.distribution.GammaDistribution
-
Creates a gamma distribution.
- of(double, double) - Static method in class org.apache.commons.statistics.distribution.GumbelDistribution
-
Creates a Gumbel distribution.
- of(double, double) - Static method in class org.apache.commons.statistics.distribution.LaplaceDistribution
-
Creates a Laplace distribution.
- of(double, double) - Static method in class org.apache.commons.statistics.distribution.LevyDistribution
-
Creates a Levy distribution.
- of(double, double) - Static method in class org.apache.commons.statistics.distribution.LogisticDistribution
-
Creates a logistic distribution.
- of(double, double) - Static method in class org.apache.commons.statistics.distribution.LogNormalDistribution
-
Creates a log-normal distribution.
- of(double, double) - Static method in class org.apache.commons.statistics.distribution.LogUniformDistribution
-
Creates a log-uniform distribution.
- of(double, double) - Static method in class org.apache.commons.statistics.distribution.NakagamiDistribution
-
Creates a Nakagami distribution.
- of(double, double) - Static method in class org.apache.commons.statistics.distribution.NormalDistribution
-
Creates a normal distribution.
- of(double, double) - Static method in class org.apache.commons.statistics.distribution.ParetoDistribution
-
Creates a Pareto distribution.
- of(double, double) - Static method in class org.apache.commons.statistics.distribution.UniformContinuousDistribution
-
Creates a uniform continuous distribution.
- of(double, double) - Static method in class org.apache.commons.statistics.distribution.WeibullDistribution
-
Creates a Weibull distribution.
- of(double, double) - Static method in class org.apache.commons.statistics.inference.BrentOptimizer.PointValuePair
-
Create a point/objective function value pair.
- of(double, double, double) - Static method in class org.apache.commons.statistics.distribution.TriangularDistribution
-
Creates a triangular distribution.
- of(double, double, double, double) - Static method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution
-
Creates a trapezoidal distribution.
- of(double, double, double, double) - Static method in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
Creates a truncated normal distribution.
- of(int...) - Static method in class org.apache.commons.statistics.descriptive.GeometricMean
-
Returns an instance populated using the input
values
. - of(int...) - Static method in class org.apache.commons.statistics.descriptive.IntMax
-
Returns an instance populated using the input
values
. - of(int...) - Static method in class org.apache.commons.statistics.descriptive.IntMean
-
Returns an instance populated using the input
values
. - of(int...) - Static method in class org.apache.commons.statistics.descriptive.IntMin
-
Returns an instance populated using the input
values
. - of(int...) - Static method in class org.apache.commons.statistics.descriptive.IntStandardDeviation
-
Returns an instance populated using the input
values
. - of(int...) - Static method in class org.apache.commons.statistics.descriptive.IntSum
-
Returns an instance populated using the input
values
. - of(int...) - Static method in class org.apache.commons.statistics.descriptive.IntSumOfSquares
-
Returns an instance populated using the input
values
. - of(int...) - Static method in class org.apache.commons.statistics.descriptive.IntVariance
-
Returns an instance populated using the input
values
. - of(int...) - Static method in class org.apache.commons.statistics.descriptive.Kurtosis
-
Returns an instance populated using the input
values
. - of(int...) - Static method in class org.apache.commons.statistics.descriptive.Product
-
Returns an instance populated using the input
values
. - of(int...) - Static method in class org.apache.commons.statistics.descriptive.Skewness
-
Returns an instance populated using the input
values
. - of(int...) - Static method in class org.apache.commons.statistics.descriptive.SumOfCubedDeviations
-
Returns an instance populated using the input
values
. - of(int...) - Static method in class org.apache.commons.statistics.descriptive.SumOfFourthDeviations
-
Returns an instance populated using the input
values
. - of(int...) - Static method in class org.apache.commons.statistics.descriptive.SumOfLogs
-
Returns an instance populated using the input
values
. - of(int, double) - Static method in class org.apache.commons.statistics.distribution.BinomialDistribution
-
Creates a binomial distribution.
- of(int, double) - Static method in class org.apache.commons.statistics.distribution.PascalDistribution
-
Create a Pascal distribution.
- of(int, double) - Static method in class org.apache.commons.statistics.distribution.ZipfDistribution
-
Creates a Zipf distribution.
- of(int, int) - Static method in class org.apache.commons.statistics.distribution.UniformDiscreteDistribution
-
Creates a new uniform discrete distribution.
- of(int, int, int) - Static method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
Creates a hypergeometric distribution.
- of(long) - Static method in class org.apache.commons.statistics.descriptive.Int128
-
Create an instance of the
long
value. - of(long) - Static method in class org.apache.commons.statistics.descriptive.UInt96
-
Create an instance of the
long
value. - of(long...) - Static method in class org.apache.commons.statistics.descriptive.GeometricMean
-
Returns an instance populated using the input
values
. - of(long...) - Static method in class org.apache.commons.statistics.descriptive.Kurtosis
-
Returns an instance populated using the input
values
. - of(long...) - Static method in class org.apache.commons.statistics.descriptive.LongMax
-
Returns an instance populated using the input
values
. - of(long...) - Static method in class org.apache.commons.statistics.descriptive.LongMean
-
Returns an instance populated using the input
values
. - of(long...) - Static method in class org.apache.commons.statistics.descriptive.LongMin
-
Returns an instance populated using the input
values
. - of(long...) - Static method in class org.apache.commons.statistics.descriptive.LongStandardDeviation
-
Returns an instance populated using the input
values
. - of(long...) - Static method in class org.apache.commons.statistics.descriptive.LongSum
-
Returns an instance populated using the input
values
. - of(long...) - Static method in class org.apache.commons.statistics.descriptive.LongSumOfSquares
-
Returns an instance populated using the input
values
. - of(long...) - Static method in class org.apache.commons.statistics.descriptive.LongVariance
-
Returns an instance populated using the input
values
. - of(long...) - Static method in class org.apache.commons.statistics.descriptive.Product
-
Returns an instance populated using the input
values
. - of(long...) - Static method in class org.apache.commons.statistics.descriptive.Skewness
-
Returns an instance populated using the input
values
. - of(long...) - Static method in class org.apache.commons.statistics.descriptive.SumOfCubedDeviations
-
Returns an instance populated using the input
values
. - of(long...) - Static method in class org.apache.commons.statistics.descriptive.SumOfFourthDeviations
-
Returns an instance populated using the input
values
. - of(long...) - Static method in class org.apache.commons.statistics.descriptive.SumOfLogs
-
Returns an instance populated using the input
values
. - of(Set<Statistic>, double...) - Static method in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
Returns a new instance configured to compute the specified
statistics
populated using the inputvalues
. - of(Set<Statistic>, int...) - Static method in class org.apache.commons.statistics.descriptive.IntStatistics
-
Returns a new instance configured to compute the specified
statistics
populated using the inputvalues
. - of(Set<Statistic>, long...) - Static method in class org.apache.commons.statistics.descriptive.LongStatistics
-
Returns a new instance configured to compute the specified
statistics
populated using the inputvalues
. - of(Statistic...) - Static method in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
Returns a new instance configured to compute the specified
statistics
. - of(Statistic...) - Static method in class org.apache.commons.statistics.descriptive.IntStatistics
-
Returns a new instance configured to compute the specified
statistics
. - of(Statistic...) - Static method in class org.apache.commons.statistics.descriptive.LongStatistics
-
Returns a new instance configured to compute the specified
statistics
. - of(UInt96) - Static method in class org.apache.commons.statistics.descriptive.UInt128
-
Create an instance of the
UInt96
value. - omega - Variable in class org.apache.commons.statistics.distribution.NakagamiDistribution
-
The scale parameter.
- One() - Constructor for class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.One
-
No instances.
- ONE_TENTH - Static variable in class org.apache.commons.statistics.distribution.SaddlePointExpansionUtils
-
1/10.
- OneResult(double, int, double) - Constructor for class org.apache.commons.statistics.inference.KolmogorovSmirnovTest.OneResult
-
Create an instance.
- OneWayAnova - Class in org.apache.commons.statistics.inference
-
Implements one-way ANOVA (analysis of variance) statistics.
- OneWayAnova() - Constructor for class org.apache.commons.statistics.inference.OneWayAnova
-
Private constructor.
- OneWayAnova.Result - Class in org.apache.commons.statistics.inference
-
Result for the one-way ANOVA.
- optimize - Variable in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Option to optimize the best initial point(s).
- optimize(DoubleUnaryOperator, double, double, double, double) - Method in class org.apache.commons.statistics.inference.BrentOptimizer
-
Search for the minimum inside the provided interval.
- org.apache.commons.statistics.descriptive - package org.apache.commons.statistics.descriptive
-
Implementations of univariate statistics.
- org.apache.commons.statistics.distribution - package org.apache.commons.statistics.distribution
-
Implementations of common discrete and continuous probability distributions.
- org.apache.commons.statistics.inference - package org.apache.commons.statistics.inference
-
Classes providing hypothesis testing.
- org.apache.commons.statistics.ranking - package org.apache.commons.statistics.ranking
-
Classes providing rank transformations.
- OUT_OF_RANGE - Static variable in exception org.apache.commons.statistics.distribution.DistributionException
-
Error message for "out of range" condition when "x not in [a, b]".
P
- p - Variable in class org.apache.commons.statistics.inference.BaseSignificanceResult
-
p-value.
- P_DOWN_SCALE - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
The scaling threshold in the Pomeranz algorithm.
- P_SCALE_POWER - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
The power-of-2 of the up-scaling factor in the Pomeranz algorithm, n if the up-scale factor is 2^n.
- P_UP_SCALE - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
The up-scaling factor in the Pomeranz algorithm.
- pairedStatistic(double[], double[]) - Method in class org.apache.commons.statistics.inference.TTest
-
Computes a paired two-sample t-statistic on related samples comparing the mean difference between the samples to
mu
. - pairedTest(double[], double[]) - Method in class org.apache.commons.statistics.inference.TTest
-
Performs a paired two-sample t-test on related samples comparing the mean difference between the samples to
mu
. - parentNormal - Variable in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
Parent normal distribution.
- ParetoDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the Pareto (Type I) distribution.
- ParetoDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.ParetoDistribution
- PascalDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the Pascal distribution.
- PascalDistribution(int, double) - Constructor for class org.apache.commons.statistics.distribution.PascalDistribution
- pdf - Variable in class org.apache.commons.statistics.distribution.ParetoDistribution
-
Implementation of PDF(x).
- pdf - Variable in class org.apache.commons.statistics.distribution.UniformContinuousDistribution
-
Cache of the density.
- pelzGood(double, int) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
Computes the Pelz-Good approximation for
P(D_n >= d)
as described in Simard and L’Ecuyer (2011). - pi - Variable in class org.apache.commons.statistics.inference.UnconditionedExactTest.Result
-
Nuisance parameter.
- PI_SQUARED_OVER_SIX - Static variable in class org.apache.commons.statistics.distribution.GumbelDistribution
-
π2/6.
- PI_SQUARED_OVER_THREE - Static variable in class org.apache.commons.statistics.distribution.LogisticDistribution
-
π2/3.
- PI2 - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution
-
pi^2.
- PI2 - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
pi^2.
- PI4 - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
pi^4.
- PI6 - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
pi^6.
- pmf - Variable in class org.apache.commons.statistics.distribution.GeometricDistribution
-
Implementation of PMF(x).
- pmf - Variable in class org.apache.commons.statistics.distribution.UniformDiscreteDistribution
-
Cache of the probability.
- pmf(int) - Method in class org.apache.commons.statistics.inference.Hypergeom
-
Compute the probability mass function (PMF) at the specified value.
- pmf0 - Variable in class org.apache.commons.statistics.distribution.BinomialDistribution
-
Cached value for pmf(x=0).
- pmfn - Variable in class org.apache.commons.statistics.distribution.BinomialDistribution
-
Cached value for pmf(x=n).
- point - Variable in class org.apache.commons.statistics.inference.BrentOptimizer.PointValuePair
-
Point.
- points - Variable in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Number of initial points.
- PointValuePair(double, double) - Constructor for class org.apache.commons.statistics.inference.BrentOptimizer.PointValuePair
- PoissonDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the Poisson distribution.
- PoissonDistribution(double) - Constructor for class org.apache.commons.statistics.distribution.PoissonDistribution
- pomeranz(double, int) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
Computes the Pomeranz approximation for
P(D_n < d)
using the method as described in Simard and L’Ecuyer (2011). - populationSize - Variable in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
The population size.
- position - Variable in class org.apache.commons.statistics.ranking.NaturalRanking.DataPosition
-
Data position.
- position0(double, int) - Method in enum org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
-
Finds the real-valued position for calculation of the quantile.
- pow(DD, int, long[]) - Method in interface org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.One.ScaledPower
-
Compute the number
x
raised to the powern
. - pow2(double) - Static method in class org.apache.commons.statistics.inference.OneWayAnova
-
Compute
x^2
. - pow3(double) - Static method in class org.apache.commons.statistics.descriptive.SumOfCubedDeviations
-
Compute
x^3
. - pow4(double) - Static method in class org.apache.commons.statistics.descriptive.SumOfFourthDeviations
-
Compute
x^4
. - power(int) - Method in class org.apache.commons.statistics.inference.SquareMatrixSupport.ArrayRealSquareMatrix
- power(int) - Method in interface org.apache.commons.statistics.inference.SquareMatrixSupport.RealSquareMatrix
-
Returns the result of multiplying
this
with itselfn
times. - POWER_DEFAULT - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.One
-
Proxy for the default choice of the scaled power function.
- prob - Variable in class org.apache.commons.statistics.inference.Hypergeom
-
Cached probability values.
- probabilities(int) - Static method in class org.apache.commons.statistics.descriptive.Quantile
-
Generate
n
evenly spaced probabilities in the range[0, 1]
. - probabilities(int, double, double) - Static method in class org.apache.commons.statistics.descriptive.Quantile
-
Generate
n
evenly spaced probabilities in the range[p1, p2]
. - probability(double, double) - Method in class org.apache.commons.statistics.distribution.AbstractContinuousDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(x0 < X <= x1)
. - probability(double, double) - Method in interface org.apache.commons.statistics.distribution.ContinuousDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(x0 < X <= x1)
. - probability(double, double) - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.HalfNormalDistribution
- probability(double, double) - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.RegularFoldedNormalDistribution
- probability(double, double) - Method in class org.apache.commons.statistics.distribution.LogNormalDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(x0 < X <= x1)
. - probability(double, double) - Method in class org.apache.commons.statistics.distribution.NormalDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(x0 < X <= x1)
. - probability(double, double) - Method in class org.apache.commons.statistics.distribution.TDistribution.NormalTDistribution
- probability(double, double) - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.DelegatedTrapezoidalDistribution
- probability(double, double) - Method in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(x0 < X <= x1)
. - probability(double, double) - Method in class org.apache.commons.statistics.distribution.UniformContinuousDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(x0 < X <= x1)
. - probability(int) - Method in class org.apache.commons.statistics.distribution.BinomialDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X = x)
. - probability(int) - Method in interface org.apache.commons.statistics.distribution.DiscreteDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X = x)
. - probability(int) - Method in class org.apache.commons.statistics.distribution.GeometricDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X = x)
. - probability(int) - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X = x)
. - probability(int) - Method in class org.apache.commons.statistics.distribution.PascalDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X = x)
. - probability(int) - Method in class org.apache.commons.statistics.distribution.PoissonDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X = x)
. - probability(int) - Method in class org.apache.commons.statistics.distribution.UniformDiscreteDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X = x)
. - probability(int) - Method in class org.apache.commons.statistics.distribution.ZipfDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X = x)
. - probability(int, int) - Method in class org.apache.commons.statistics.distribution.AbstractDiscreteDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(x0 < X <= x1)
. - probability(int, int) - Method in interface org.apache.commons.statistics.distribution.DiscreteDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(x0 < X <= x1)
. - probability(int, int) - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(x0 < X <= x1)
. - probability(int, int) - Method in class org.apache.commons.statistics.distribution.UniformDiscreteDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(x0 < X <= x1)
. - probabilityOfSuccess - Variable in class org.apache.commons.statistics.distribution.BinomialDistribution
-
The probability of success.
- probabilityOfSuccess - Variable in class org.apache.commons.statistics.distribution.GeometricDistribution
-
The probability of success.
- probabilityOfSuccess - Variable in class org.apache.commons.statistics.distribution.PascalDistribution
-
The probability of success.
- probabilityOfSuccessPowNumOfSuccesses - Variable in class org.apache.commons.statistics.distribution.PascalDistribution
-
The value of
p^n
, wherep
is the probability of success andn
is the number of successes, stored for faster computation. - product - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
-
The
Product
constructor. - product - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
The
Product
implementation. - product - Variable in class org.apache.commons.statistics.descriptive.IntStatistics.Builder
-
The
Product
constructor. - product - Variable in class org.apache.commons.statistics.descriptive.IntStatistics
-
The
Product
implementation. - product - Variable in class org.apache.commons.statistics.descriptive.LongStatistics.Builder
-
The
Product
constructor. - product - Variable in class org.apache.commons.statistics.descriptive.LongStatistics
-
The
Product
implementation. - Product - Class in org.apache.commons.statistics.descriptive
-
Returns the product of the available values.
- Product() - Constructor for class org.apache.commons.statistics.descriptive.Product
-
Create an instance.
- PRODUCT - org.apache.commons.statistics.descriptive.Statistic
-
Product.
- productValue - Variable in class org.apache.commons.statistics.descriptive.Product
-
Product of all values.
- pValueMethod - Variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Method to compute the p-value.
- pValueMethod - Variable in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
Method to compute the p-value.
- pValueMethod - Variable in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Method to compute the p-value.
- PValueMethod - Enum in org.apache.commons.statistics.inference
-
Represents a method for computing a p-value for a test statistic.
- PValueMethod() - Constructor for enum org.apache.commons.statistics.inference.PValueMethod
Q
- Quantile - Class in org.apache.commons.statistics.descriptive
-
Provides quantile computation.
- Quantile(boolean, NaNPolicy, Quantile.EstimationMethod) - Constructor for class org.apache.commons.statistics.descriptive.Quantile
- Quantile.EstimationMethod - Enum in org.apache.commons.statistics.descriptive
-
Estimation methods for a quantile.
R
- RANDOM - org.apache.commons.statistics.ranking.TiesStrategy
-
Tied values are assigned a unique random integral rank from among the applicable values.
- randomIntFunction - Variable in class org.apache.commons.statistics.ranking.NaturalRanking
-
Source of randomness when ties strategy is RANDOM.
- RANKING - Static variable in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
Ranking instance.
- RANKING - Static variable in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Ranking instance.
- RankingAlgorithm - Interface in org.apache.commons.statistics.ranking
-
Interface representing a rank transformation.
- RegularFoldedNormalDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.FoldedNormalDistribution.RegularFoldedNormalDistribution
- RegularTrapezoidalDistribution(double, double, double, double) - Constructor for class org.apache.commons.statistics.distribution.TrapezoidalDistribution.RegularTrapezoidalDistribution
- reject(double) - Method in interface org.apache.commons.statistics.inference.SignificanceResult
-
Returns true iff the null hypothesis can be rejected with
100 * (1 - alpha)
percent confidence. - REJECTION_THRESHOLD - Static variable in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
The threshold to switch to a rejection sampler.
- relativeThreshold - Variable in class org.apache.commons.statistics.inference.BrentOptimizer
-
Relative threshold.
- REMOVED - org.apache.commons.statistics.ranking.NaNStrategy
-
NaNs are removed before rank transform is applied.
- replaceWorst(double, double) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest.Candidates
-
Replace the worst candidate.
- RESCALE - Static variable in class org.apache.commons.statistics.descriptive.FirstMoment
-
The rescale constant.
- resolveTie(double[], NaturalRanking.IntList, int) - Method in class org.apache.commons.statistics.ranking.NaturalRanking
-
Resolve a sequence of ties, using the configured
TiesStrategy
. - Result(double) - Constructor for class org.apache.commons.statistics.inference.UnconditionedExactTest.Result
-
Create an instance where all tables are more extreme, i.e.
- Result(double, boolean, boolean, double) - Constructor for class org.apache.commons.statistics.inference.WilcoxonSignedRankTest.Result
-
Create an instance.
- Result(double, boolean, double) - Constructor for class org.apache.commons.statistics.inference.MannWhitneyUTest.Result
-
Create an instance.
- Result(double, double, double) - Constructor for class org.apache.commons.statistics.inference.TTest.Result
-
Create an instance.
- Result(double, double, double) - Constructor for class org.apache.commons.statistics.inference.UnconditionedExactTest.Result
- Result(int, long, double, double, double, double, double) - Constructor for class org.apache.commons.statistics.inference.OneWayAnova.Result
- rng - Variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Source of randomness.
- ROOT_2_PI - Static variable in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
Normalisation constant 2 / sqrt(2 pi) = sqrt(2 / pi).
- ROOT_HALF_PI - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
sqrt(pi/2).
- ROOT_PI_2 - Static variable in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
Normalisation constant sqrt(2 pi) / 2 = sqrt(pi / 2).
- ROOT_PI_DIV_TWO - Static variable in class org.apache.commons.statistics.distribution.Constants
-
sqrt(pi / 2).
- ROOT_TWO - Static variable in class org.apache.commons.statistics.distribution.Constants
-
sqrt(2).
- ROOT_TWO_DIV_PI - Static variable in class org.apache.commons.statistics.distribution.Constants
-
sqrt(2 / pi).
- ROOT_TWO_PI - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution
-
sqrt(2*pi).
- ROOT_TWO_PI - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
sqrt(2*pi).
- ROOT2 - Static variable in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
sqrt(2).
- roundToInteger(double) - Static method in class org.apache.commons.statistics.descriptive.IntMath
-
Get the whole number that is the nearest to x, with ties rounding towards positive infinity.
- ROW - Static variable in class org.apache.commons.statistics.inference.ChiSquareTest
-
Name for the row.
S
- SaddlePointExpansionUtils - Class in org.apache.commons.statistics.distribution
-
Utility class used by various distributions to accurately compute their respective probability mass functions.
- SaddlePointExpansionUtils() - Constructor for class org.apache.commons.statistics.distribution.SaddlePointExpansionUtils
-
Forbid construction.
- sample() - Method in interface org.apache.commons.statistics.distribution.ContinuousDistribution.Sampler
-
Generates a random value sampled from this distribution.
- sample() - Method in interface org.apache.commons.statistics.distribution.DiscreteDistribution.Sampler
-
Generates a random value sampled from this distribution.
- SAMPLE_1_NAME - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Name for sample 1.
- SAMPLE_2_NAME - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Name for sample 2.
- samples() - Method in interface org.apache.commons.statistics.distribution.ContinuousDistribution.Sampler
-
Returns an effectively unlimited stream of
double
sample values. - samples() - Method in interface org.apache.commons.statistics.distribution.DiscreteDistribution.Sampler
-
Returns an effectively unlimited stream of
int
sample values. - samples(long) - Method in interface org.apache.commons.statistics.distribution.ContinuousDistribution.Sampler
-
Returns a stream producing the given
streamSize
number ofdouble
sample values. - samples(long) - Method in interface org.apache.commons.statistics.distribution.DiscreteDistribution.Sampler
-
Returns a stream producing the given
streamSize
number ofint
sample values. - sampleSize - Variable in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
The sample size.
- sc - Variable in class org.apache.commons.statistics.descriptive.Skewness
-
An instance of
SumOfCubedDeviations
, which is used to compute the skewness. - scale - Variable in class org.apache.commons.statistics.distribution.CauchyDistribution
-
The scale of this distribution.
- scale - Variable in class org.apache.commons.statistics.distribution.GammaDistribution
-
The scale parameter.
- scale - Variable in class org.apache.commons.statistics.distribution.LogisticDistribution
-
Scale parameter.
- scale - Variable in class org.apache.commons.statistics.distribution.ParetoDistribution
-
The scale parameter of this distribution.
- scale - Variable in class org.apache.commons.statistics.distribution.WeibullDistribution
-
The scale parameter.
- scale() - Method in class org.apache.commons.statistics.inference.SquareMatrixSupport.ArrayRealSquareMatrix
- scale() - Method in interface org.apache.commons.statistics.inference.SquareMatrixSupport.RealSquareMatrix
-
Gets the scale of the matrix values.
- SCALE_DOWN - Static variable in class org.apache.commons.statistics.distribution.ExtendedPrecision
-
Scale down by 2^600.
- SCALE_THRESHOLD - Static variable in class org.apache.commons.statistics.inference.SquareMatrixSupport.ArrayRealSquareMatrix
-
The scaling threshold.
- SCALE_UP - Static variable in class org.apache.commons.statistics.distribution.ExtendedPrecision
-
Scale up by 2^600.
- scale2 - Variable in class org.apache.commons.statistics.distribution.CauchyDistribution
-
Density factor (scale^2).
- scaleOverPi - Variable in class org.apache.commons.statistics.distribution.CauchyDistribution
-
Density factor (scale / pi).
- SD_MAX_TERMS - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.One
-
Maximum number of term for the Smirnov-Dwass algorithm.
- SD_MIN_N - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.One
-
Minimum sample size for the Smirnov-Dwass algorithm.
- SD_SUM_PRECISION_BITS - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.One
-
Number of bits of precision in the sum of terms Aj.
- sdSqrt2 - Variable in class org.apache.commons.statistics.distribution.NormalDistribution
-
Standard deviation multiplied by sqrt(2).
- sdSqrt2pi - Variable in class org.apache.commons.statistics.distribution.NormalDistribution
-
Standard deviation multiplied by sqrt(2 pi).
- search(DoubleUnaryOperator, double, double, double, double) - Method in class org.apache.commons.statistics.inference.BracketFinder
-
Search downhill from the initial points to obtain new points that bracket a local minimum of the function.
- searchAscending(int, int, double, IntToDoubleFunction) - Static method in class org.apache.commons.statistics.inference.Searches
-
Conduct a search between
a
inclusive andb
inclusive to find the highest index wherevalue <= x
. - searchDescending(int, int, double, IntToDoubleFunction) - Static method in class org.apache.commons.statistics.inference.Searches
-
Conduct a search between
a
inclusive andb
inclusive to find the lowest index wherevalue <= x
. - Searches - Class in org.apache.commons.statistics.inference
-
Search utility methods.
- Searches() - Constructor for class org.apache.commons.statistics.inference.Searches
-
No instances.
- searchPlateau(boolean, double, double) - Method in class org.apache.commons.statistics.distribution.AbstractContinuousDistribution
-
Test the probability function for a plateau at the point x.
- selectMethod(PValueMethod, int) - Static method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Select the method to compute the p-value.
- SEQUENTIAL - org.apache.commons.statistics.ranking.TiesStrategy
-
Ties are assigned ranks in order of occurrence in the original array.
- serialVersionUID - Static variable in exception org.apache.commons.statistics.distribution.DistributionException
-
Serializable version identifier.
- serialVersionUID - Static variable in exception org.apache.commons.statistics.inference.InferenceException
-
Serializable version identifier.
- setBiased(boolean) - Method in class org.apache.commons.statistics.descriptive.IntStandardDeviation
-
Sets the value of the biased flag.
- setBiased(boolean) - Method in class org.apache.commons.statistics.descriptive.IntVariance
-
Sets the value of the biased flag.
- setBiased(boolean) - Method in class org.apache.commons.statistics.descriptive.Kurtosis
-
Sets the value of the biased flag.
- setBiased(boolean) - Method in class org.apache.commons.statistics.descriptive.LongStandardDeviation
-
Sets the value of the biased flag.
- setBiased(boolean) - Method in class org.apache.commons.statistics.descriptive.LongVariance
-
Sets the value of the biased flag.
- setBiased(boolean) - Method in class org.apache.commons.statistics.descriptive.Skewness
-
Sets the value of the biased flag.
- setBiased(boolean) - Method in class org.apache.commons.statistics.descriptive.StandardDeviation
-
Sets the value of the biased flag.
- setBiased(boolean) - Method in class org.apache.commons.statistics.descriptive.Variance
-
Sets the value of the biased flag.
- setConfiguration(StatisticsConfiguration) - Method in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
-
Sets the statistics configuration options for computation of statistics.
- setConfiguration(StatisticsConfiguration) - Method in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
Sets the statistics configuration.
- setConfiguration(StatisticsConfiguration) - Method in class org.apache.commons.statistics.descriptive.IntStatistics.Builder
-
Sets the statistics configuration options for computation of statistics.
- setConfiguration(StatisticsConfiguration) - Method in class org.apache.commons.statistics.descriptive.IntStatistics
-
Sets the statistics configuration.
- setConfiguration(StatisticsConfiguration) - Method in class org.apache.commons.statistics.descriptive.LongStatistics.Builder
-
Sets the statistics configuration options for computation of statistics.
- setConfiguration(StatisticsConfiguration) - Method in class org.apache.commons.statistics.descriptive.LongStatistics
-
Sets the statistics configuration.
- sf(double, int) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.One
-
Calculates complementary probability
P[D_n^+ >= x]
, or survival function (SF), for the one-sided one-sample Kolmogorov-Smirnov distribution. - sf(double, int) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
Calculates complementary probability
P[D_n >= x]
for the two-sided one-sample Kolmogorov-Smirnov distribution. - sf(double, int, KolmogorovSmirnovDistribution.One.ScaledPower) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.One
-
Calculates complementary probability
P[D_n^+ >= x]
, or survival function (SF), for the one-sided one-sample Kolmogorov-Smirnov distribution. - sf(int) - Method in class org.apache.commons.statistics.inference.Hypergeom
-
Compute the survival function (SF) at the specified value.
- sf(int, int, int) - Static method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Compute the survival function of the Wilcoxon signed rank W+ statistic.
- sf(int, int, int, int, double) - Static method in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
Compute the survival function of the Mann-Whitney U1 statistic.
- sf0 - Variable in class org.apache.commons.statistics.distribution.GeometricDistribution
-
Value of survival probability for x=0.
- sf0 - Variable in class org.apache.commons.statistics.distribution.UniformDiscreteDistribution
-
Value of survival probability for x=0.
- sfAsymptotic(double, int) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.One
-
Calculates complementary probability
P[D_n^+ >= x]
, or survival function (SF), for the one-sided one-sample Kolmogorov-Smirnov distribution. - sfB - Variable in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.RegularTrapezoidalDistribution
-
Survival probability at b.
- sfBeta - Variable in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
Stored value of
parentNormal.survivalProbability(upper)
. - sfC - Variable in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.RegularTrapezoidalDistribution
-
Survival probability at c.
- sfExact(double, int) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.One
-
Calculates exact cases for the complementary probability
P[D_n^+ >= x]
the one-sided one-sample Kolmogorov-Smirnov distribution. - sfExact(double, int) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
Calculates exact cases for the complementary probability
P[D_n >= x]
the two-sided one-sample Kolmogorov-Smirnov distribution. - sfMode - Variable in class org.apache.commons.statistics.distribution.TriangularDistribution
-
Survival probability at the mode.
- shape - Variable in class org.apache.commons.statistics.distribution.GammaDistribution
-
The shape parameter.
- shape - Variable in class org.apache.commons.statistics.distribution.ParetoDistribution
-
The shape parameter of this distribution.
- shape - Variable in class org.apache.commons.statistics.distribution.WeibullDistribution
-
The shape parameter.
- shapeOverScale - Variable in class org.apache.commons.statistics.distribution.WeibullDistribution
-
shape / scale.
- shuffle(IntUnaryOperator) - Method in class org.apache.commons.statistics.ranking.NaturalRanking.IntList
-
Shuffle the list.
- sigma - Variable in class org.apache.commons.statistics.distribution.FoldedNormalDistribution
-
The scale.
- sigma - Variable in class org.apache.commons.statistics.distribution.LogNormalDistribution
-
The sigma parameter of this distribution.
- sigmaSqrt2 - Variable in class org.apache.commons.statistics.distribution.FoldedNormalDistribution
-
The scale multiplied by sqrt(2).
- sigmaSqrt2 - Variable in class org.apache.commons.statistics.distribution.LogNormalDistribution
-
Sigma multiplied by sqrt(2).
- sigmaSqrt2pi - Variable in class org.apache.commons.statistics.distribution.FoldedNormalDistribution
-
The scale multiplied by sqrt(2 pi).
- sigmaSqrt2Pi - Variable in class org.apache.commons.statistics.distribution.LogNormalDistribution
-
Sigma multiplied by sqrt(2 * pi).
- sign - Variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest.OneResult
-
Sign of the statistic.
- SignificanceResult - Interface in org.apache.commons.statistics.inference
-
Contains the result of a test for significance.
- significantTies - Variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest.TwoResult
-
Flag to indicate there were significant ties.
- size - Variable in class org.apache.commons.statistics.inference.UnconditionedExactTest.Candidates
-
Current size of the list.
- size - Variable in class org.apache.commons.statistics.inference.UnconditionedExactTest.XYList
-
The size of the list.
- size - Variable in class org.apache.commons.statistics.ranking.NaturalRanking.IntList
-
The size of the list.
- size() - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest.XYList
-
Gets the number of elements in the list.
- size() - Method in class org.apache.commons.statistics.ranking.NaturalRanking.IntList
-
Gets the number of elements in the list.
- Skewness - Class in org.apache.commons.statistics.descriptive
-
Computes the skewness of the available values.
- Skewness() - Constructor for class org.apache.commons.statistics.descriptive.Skewness
-
Create an instance.
- Skewness(SumOfCubedDeviations) - Constructor for class org.apache.commons.statistics.descriptive.Skewness
-
Creates an instance with the sum of cubed deviations from the mean.
- SKEWNESS - org.apache.commons.statistics.descriptive.Statistic
-
Skewness.
- SMALL - Static variable in class org.apache.commons.statistics.distribution.ExtendedPrecision
-
Threshold for a small number that may underflow when squared.
- SMALL_N - Static variable in class org.apache.commons.statistics.descriptive.IntMean
-
Limit for small sample size where the sum can exactly map to a double.
- SMALL_SAMPLE - Static variable in class org.apache.commons.statistics.descriptive.IntSumOfSquares
-
Small array sample size.
- SMALL_SAMPLE - Static variable in class org.apache.commons.statistics.descriptive.IntVariance
-
Small array sample size.
- SMALL_SUM - Static variable in class org.apache.commons.statistics.descriptive.LongMean
-
Limit where the absolute sum can exactly map to a double.
- solveInverseProbability(IntUnaryOperator, int, int) - Static method in class org.apache.commons.statistics.distribution.AbstractDiscreteDistribution
-
This is a utility function used by
AbstractDiscreteDistribution.inverseProbability(double, double, boolean)
. - SOLVER_ABSOLUTE_ACCURACY - Static variable in class org.apache.commons.statistics.distribution.AbstractContinuousDistribution
-
BrentSolver absolute accuracy.
- SOLVER_FUNCTION_VALUE_ACCURACY - Static variable in class org.apache.commons.statistics.distribution.AbstractContinuousDistribution
-
BrentSolver function value accuracy.
- SOLVER_RELATIVE_ACCURACY - Static variable in class org.apache.commons.statistics.distribution.AbstractContinuousDistribution
-
BrentSolver relative accuracy.
- SOLVER_RELATIVE_EPS - Static variable in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Relative epsilon for the Brent solver.
- sort(double[], String) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Sort the input array.
- splitX(int, double, double[]) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.One
-
Compute exactly
x = (k + alpha) / n
withk
an integer andalpha in [0, 1)
. - sq - Variable in class org.apache.commons.statistics.descriptive.Kurtosis
-
An instance of
SumOfFourthDeviations
, which is used to compute the kurtosis. - SQRT2PI - Static variable in class org.apache.commons.statistics.distribution.ExtendedPrecision
-
sqrt(2 pi) as a double-double number.
- SQRT2PI - Static variable in class org.apache.commons.statistics.distribution.LogNormalDistribution
-
√(2 π).
- sqrt2xx(double) - Static method in class org.apache.commons.statistics.distribution.ExtendedPrecision
-
Compute
sqrt(2 * x * x)
. - square(BigInteger) - Static method in class org.apache.commons.statistics.descriptive.IntVariance
-
Convenience method to square a BigInteger.
- square(BigInteger) - Static method in class org.apache.commons.statistics.descriptive.LongVariance
-
Convenience method to square a BigInteger.
- squareHigh(long) - Static method in class org.apache.commons.statistics.descriptive.IntMath
-
Square the values as if an unsigned 64-bit long to produce the high 64-bits of the 128-bit unsigned result.
- squareLow() - Method in class org.apache.commons.statistics.descriptive.Int128
-
Compute the square of the low 64-bits of this number.
- SquareMatrixSupport - Class in org.apache.commons.statistics.inference
-
Provide support for square matrix basic algebraic operations.
- SquareMatrixSupport() - Constructor for class org.apache.commons.statistics.inference.SquareMatrixSupport
-
No instances.
- SquareMatrixSupport.ArrayRealSquareMatrix - Class in org.apache.commons.statistics.inference
-
Implementation of
SquareMatrixSupport.RealSquareMatrix
using adouble[]
array to store entries. - SquareMatrixSupport.RealSquareMatrix - Interface in org.apache.commons.statistics.inference
-
Define a real-valued square matrix.
- ss - Variable in class org.apache.commons.statistics.descriptive.StandardDeviation
-
An instance of
SumOfSquaredDeviations
, which is used to compute the standard deviation. - ss - Variable in class org.apache.commons.statistics.descriptive.SumOfSquares
-
Sum of squares of all values.
- ss - Variable in class org.apache.commons.statistics.descriptive.Variance
-
An instance of
SumOfSquaredDeviations
, which is used to compute the variance. - STANDARD_DEVIATION - org.apache.commons.statistics.descriptive.Statistic
-
Standard deviation.
- STANDARD_NORMAL - Static variable in class org.apache.commons.statistics.distribution.TDistribution.NormalTDistribution
-
A standard normal distribution used for calculations.
- standardDeviation - Variable in class org.apache.commons.statistics.distribution.NormalDistribution
-
Standard deviation of this distribution.
- StandardDeviation - Class in org.apache.commons.statistics.descriptive
-
Computes the standard deviation of the available values.
- StandardDeviation() - Constructor for class org.apache.commons.statistics.descriptive.StandardDeviation
-
Create an instance.
- StandardDeviation(SumOfSquaredDeviations) - Constructor for class org.apache.commons.statistics.descriptive.StandardDeviation
-
Creates an instance with the sum of squared deviations from the mean.
- statistic - Variable in class org.apache.commons.statistics.inference.BaseSignificanceResult
-
Test statistics.
- statistic(double[]) - Method in class org.apache.commons.statistics.inference.TTest
-
Computes a one-sample t statistic comparing the mean of the sample to
mu
. - statistic(double[]) - Method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Computes the Wilcoxon signed ranked statistic comparing the differences between sample values
z = x - y
tomu
. - statistic(double[], double[]) - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Computes the two-sample Kolmogorov-Smirnov test statistic.
- statistic(double[], double[]) - Method in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
Computes the Mann-Whitney U statistic comparing two independent samples possibly of different length.
- statistic(double[], double[]) - Method in class org.apache.commons.statistics.inference.TTest
-
Computes a two-sample t statistic on independent samples comparing the difference in means of the samples to
mu
. - statistic(double[], double[]) - Method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Computes the Wilcoxon signed ranked statistic comparing the differences between two related samples or repeated measurements on a single sample.
- statistic(double[], long[]) - Method in class org.apache.commons.statistics.inference.ChiSquareTest
-
Computes the chi-square goodness-of-fit statistic comparing
observed
andexpected
frequency counts. - statistic(double[], long[]) - Method in class org.apache.commons.statistics.inference.GTest
-
Computes the G-test goodness-of-fit statistic comparing
observed
andexpected
frequency counts. - statistic(double[], DoubleUnaryOperator) - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Computes the one-sample Kolmogorov-Smirnov test statistic.
- statistic(double, double, long) - Method in class org.apache.commons.statistics.inference.TTest
-
Computes a one-sample t statistic comparing the mean of the dataset to
mu
. - statistic(double, double, long, double, double, long) - Method in class org.apache.commons.statistics.inference.TTest
-
Computes a two-sample t statistic on independent samples comparing the difference in means of the datasets to
mu
. - statistic(int[][]) - Method in class org.apache.commons.statistics.inference.FisherExactTest
-
Compute the prior odds ratio for the 2-by-2 contingency table.
- statistic(int[][]) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Compute the statistic for the unconditioned exact test.
- statistic(long[]) - Method in class org.apache.commons.statistics.inference.ChiSquareTest
-
Computes the chi-square goodness-of-fit statistic comparing the
observed
counts to a uniform expected value (each category is equally likely). - statistic(long[]) - Method in class org.apache.commons.statistics.inference.GTest
-
Computes the G-test goodness-of-fit statistic comparing the
observed
counts to a uniform expected value (each category is equally likely). - statistic(long[][]) - Method in class org.apache.commons.statistics.inference.ChiSquareTest
-
Computes the chi-square statistic associated with a chi-square test of independence based on the input
counts
array, viewed as a two-way table in row-major format. - statistic(long[][]) - Method in class org.apache.commons.statistics.inference.GTest
-
Computes a G-test statistic associated with a G-test of independence based on the input
counts
array, viewed as a two-way table. - statistic(long[], long[]) - Method in class org.apache.commons.statistics.inference.ChiSquareTest
-
Computes a chi-square statistic associated with a chi-square test of independence of frequency counts in
observed1
andobserved2
. - statistic(Collection<double[]>) - Method in class org.apache.commons.statistics.inference.OneWayAnova
-
Computes the F statistic for an ANOVA test for a collection of category data, evaluating the null hypothesis that there is no difference among the means of the data categories.
- Statistic - Enum in org.apache.commons.statistics.descriptive
-
A statistic that can be computed on univariate data, for example a stream of
double
values. - Statistic() - Constructor for enum org.apache.commons.statistics.descriptive.Statistic
- StatisticAccumulator<T extends StatisticResult> - Interface in org.apache.commons.statistics.descriptive
-
A mutable result container that accumulates a
StatisticResult
. - statisticBoschloo(int, int, int, int) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Compute the statistic using Fisher's p-value (also known as Boschloo's test).
- statisticBoschlooTwoSided(Hypergeom, int) - Static method in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Compute the two-sided statistic using Fisher's p-value (also known as Boschloo's test).
- StatisticResult - Interface in org.apache.commons.statistics.descriptive
-
Represents the result of a statistic computed over a set of values.
- Statistics - Class in org.apache.commons.statistics.descriptive
-
Utility methods for statistics.
- Statistics() - Constructor for class org.apache.commons.statistics.descriptive.Statistics
-
No instances.
- StatisticsConfiguration - Class in org.apache.commons.statistics.descriptive
-
Configuration for computation of statistics.
- StatisticsConfiguration(boolean) - Constructor for class org.apache.commons.statistics.descriptive.StatisticsConfiguration
-
Create an instance.
- StatisticUtils - Class in org.apache.commons.statistics.inference
-
Utility computation methods.
- StatisticUtils() - Constructor for class org.apache.commons.statistics.inference.StatisticUtils
-
No instances.
- statisticZ(int, int, int, int, boolean) - Static method in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Compute the statistic from a Z-test.
- STIRLING_ERROR_THRESHOLD - Static variable in class org.apache.commons.statistics.distribution.SaddlePointExpansionUtils
-
The threshold value for switching the method to compute th Stirling error.
- STRICT - org.apache.commons.statistics.inference.Inequality
-
Represents a strict inequality.
- strictInequality - Variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Use a strict inequality for the two-sample exact p-value.
- StudentsTDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.TDistribution.StudentsTDistribution
- subtract(double[], double) - Static method in class org.apache.commons.statistics.inference.StatisticUtils
-
Compute
x - y
. - subtract(UInt128) - Method in class org.apache.commons.statistics.descriptive.UInt128
-
Subtracts the value.
- subtract(UInt128) - Method in class org.apache.commons.statistics.descriptive.UInt192
-
Subtracts the value.
- sum - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
-
The
Sum
constructor. - sum - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
The
Sum
implementation. - sum - Variable in class org.apache.commons.statistics.descriptive.IntMean
-
Sum of the values.
- sum - Variable in class org.apache.commons.statistics.descriptive.IntStandardDeviation
-
Sum of the values.
- sum - Variable in class org.apache.commons.statistics.descriptive.IntStatistics.Builder
-
The
IntSum
constructor. - sum - Variable in class org.apache.commons.statistics.descriptive.IntStatistics
-
The
IntSum
implementation. - sum - Variable in class org.apache.commons.statistics.descriptive.IntSum
-
Sum of the values.
- sum - Variable in class org.apache.commons.statistics.descriptive.IntVariance
-
Sum of the values.
- sum - Variable in class org.apache.commons.statistics.descriptive.LongMean
-
Sum of the values.
- sum - Variable in class org.apache.commons.statistics.descriptive.LongStandardDeviation
-
Sum of the values.
- sum - Variable in class org.apache.commons.statistics.descriptive.LongStatistics.Builder
-
The
LongSum
constructor. - sum - Variable in class org.apache.commons.statistics.descriptive.LongStatistics
-
The
LongSum
implementation. - sum - Variable in class org.apache.commons.statistics.descriptive.LongSum
-
Sum of the values.
- sum - Variable in class org.apache.commons.statistics.descriptive.LongVariance
-
Sum of the values.
- Sum - Class in org.apache.commons.statistics.descriptive
-
Returns the sum of the available values.
- Sum() - Constructor for class org.apache.commons.statistics.descriptive.Sum
-
Create an instance.
- Sum(Sum) - Constructor for class org.apache.commons.statistics.descriptive.Sum
-
Create an instance using the specified
sum
. - SUM - org.apache.commons.statistics.descriptive.Statistic
-
Sum.
- SUM_OF_LOGS - org.apache.commons.statistics.descriptive.Statistic
-
Sum of the natural logarithm of values.
- SUM_OF_SQUARES - org.apache.commons.statistics.descriptive.Statistic
-
Sum of the squared values.
- SUM_PRECISION_BITS - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.One
-
Number of bits of precision in the sum of terms Aj.
- sumCubedDev - Variable in class org.apache.commons.statistics.descriptive.SumOfCubedDeviations
-
Sum of cubed deviations of the values that have been added.
- sumFourthDev - Variable in class org.apache.commons.statistics.descriptive.SumOfFourthDeviations
-
Sum of forth deviations of the values that have been added.
- SumOfCubedDeviations - Class in org.apache.commons.statistics.descriptive
-
Computes the sum of cubed deviations from the sample mean.
- SumOfCubedDeviations() - Constructor for class org.apache.commons.statistics.descriptive.SumOfCubedDeviations
-
Create an instance.
- SumOfCubedDeviations(double, double, double, long) - Constructor for class org.apache.commons.statistics.descriptive.SumOfCubedDeviations
-
Create an instance with the given sum of cubed and squared deviations, and first moment.
- SumOfCubedDeviations(double, SumOfSquaredDeviations) - Constructor for class org.apache.commons.statistics.descriptive.SumOfCubedDeviations
-
Create an instance with the given sum of cubed and squared deviations.
- SumOfCubedDeviations(SumOfCubedDeviations) - Constructor for class org.apache.commons.statistics.descriptive.SumOfCubedDeviations
-
Copy constructor.
- SumOfFourthDeviations - Class in org.apache.commons.statistics.descriptive
-
Computes the sum of fourth deviations from the sample mean.
- SumOfFourthDeviations() - Constructor for class org.apache.commons.statistics.descriptive.SumOfFourthDeviations
-
Create an instance.
- SumOfFourthDeviations(double, double, double, double, long) - Constructor for class org.apache.commons.statistics.descriptive.SumOfFourthDeviations
-
Create an instance with the given sum of cubed and squared deviations, and first moment.
- SumOfFourthDeviations(double, SumOfCubedDeviations) - Constructor for class org.apache.commons.statistics.descriptive.SumOfFourthDeviations
-
Create an instance with the given sum of fourth and squared deviations.
- sumOfLogs - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
-
The
SumOfLogs
constructor. - sumOfLogs - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
The
SumOfLogs
implementation. - sumOfLogs - Variable in class org.apache.commons.statistics.descriptive.GeometricMean
-
Sum of logs used to compute the geometric mean.
- sumOfLogs - Variable in class org.apache.commons.statistics.descriptive.IntStatistics.Builder
-
The
SumOfLogs
constructor. - sumOfLogs - Variable in class org.apache.commons.statistics.descriptive.IntStatistics
-
The
SumOfLogs
implementation. - sumOfLogs - Variable in class org.apache.commons.statistics.descriptive.LongStatistics.Builder
-
The
SumOfLogs
constructor. - sumOfLogs - Variable in class org.apache.commons.statistics.descriptive.LongStatistics
-
The
SumOfLogs
implementation. - SumOfLogs - Class in org.apache.commons.statistics.descriptive
-
Returns the sum of the
natural logarithm
of available values. - SumOfLogs() - Constructor for class org.apache.commons.statistics.descriptive.SumOfLogs
-
Create an instance.
- SumOfSquaredDeviations - Class in org.apache.commons.statistics.descriptive
-
Computes the sum of squared deviations from the sample mean.
- SumOfSquaredDeviations() - Constructor for class org.apache.commons.statistics.descriptive.SumOfSquaredDeviations
-
Create an instance.
- SumOfSquaredDeviations(double, double, long) - Constructor for class org.apache.commons.statistics.descriptive.SumOfSquaredDeviations
-
Create an instance with the given sum of squared deviations and first moment.
- SumOfSquaredDeviations(double, FirstMoment) - Constructor for class org.apache.commons.statistics.descriptive.SumOfSquaredDeviations
-
Create an instance with the given sum of squared deviations and first moment.
- SumOfSquaredDeviations(SumOfSquaredDeviations) - Constructor for class org.apache.commons.statistics.descriptive.SumOfSquaredDeviations
-
Copy constructor.
- sumOfSquares - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
-
The
SumOfSquares
constructor. - sumOfSquares - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
The
SumOfSquares
implementation. - sumOfSquares - Variable in class org.apache.commons.statistics.descriptive.IntStatistics.Builder
-
The
IntSumOfSquares
constructor. - sumOfSquares - Variable in class org.apache.commons.statistics.descriptive.IntStatistics
-
The
IntSumOfSquares
implementation. - sumOfSquares - Variable in class org.apache.commons.statistics.descriptive.LongStatistics.Builder
-
The
LongSumOfSquares
constructor. - sumOfSquares - Variable in class org.apache.commons.statistics.descriptive.LongStatistics
-
The
LongSumOfSquares
implementation. - SumOfSquares - Class in org.apache.commons.statistics.descriptive
-
Returns the sum of the squares of the available values.
- SumOfSquares() - Constructor for class org.apache.commons.statistics.descriptive.SumOfSquares
-
Create an instance.
- sumSq - Variable in class org.apache.commons.statistics.descriptive.IntStandardDeviation
-
Sum of the squared values.
- sumSq - Variable in class org.apache.commons.statistics.descriptive.IntSumOfSquares
-
Sum of the squared values.
- sumSq - Variable in class org.apache.commons.statistics.descriptive.IntVariance
-
Sum of the squared values.
- sumSq - Variable in class org.apache.commons.statistics.descriptive.LongStandardDeviation
-
Sum of the squared values.
- sumSq - Variable in class org.apache.commons.statistics.descriptive.LongSumOfSquares
-
Sum of the squared values.
- sumSq - Variable in class org.apache.commons.statistics.descriptive.LongVariance
-
Sum of the squared values.
- sumSquaredDev - Variable in class org.apache.commons.statistics.descriptive.SumOfSquaredDeviations
-
Sum of squared deviations of the values that have been added.
- SUPPORT_HI - Static variable in class org.apache.commons.statistics.distribution.ExponentialDistribution
-
Support upper bound.
- SUPPORT_HI - Static variable in class org.apache.commons.statistics.distribution.FDistribution
-
Support upper bound.
- SUPPORT_HI - Static variable in class org.apache.commons.statistics.distribution.GammaDistribution
-
Support upper bound.
- SUPPORT_HI - Static variable in class org.apache.commons.statistics.distribution.GumbelDistribution
-
Support upper bound.
- SUPPORT_HI - Static variable in class org.apache.commons.statistics.distribution.LogisticDistribution
-
Support upper bound.
- SUPPORT_HI - Static variable in class org.apache.commons.statistics.distribution.NakagamiDistribution
-
Support upper bound.
- SUPPORT_HI - Static variable in class org.apache.commons.statistics.distribution.WeibullDistribution
-
Support upper bound.
- SUPPORT_LO - Static variable in class org.apache.commons.statistics.distribution.ExponentialDistribution
-
Support lower bound.
- SUPPORT_LO - Static variable in class org.apache.commons.statistics.distribution.FDistribution
-
Support lower bound.
- SUPPORT_LO - Static variable in class org.apache.commons.statistics.distribution.GammaDistribution
-
Support lower bound.
- SUPPORT_LO - Static variable in class org.apache.commons.statistics.distribution.GumbelDistribution
-
Support lower bound.
- SUPPORT_LO - Static variable in class org.apache.commons.statistics.distribution.LogisticDistribution
-
Support lower bound.
- SUPPORT_LO - Static variable in class org.apache.commons.statistics.distribution.NakagamiDistribution
-
Support lower bound.
- SUPPORT_LO - Static variable in class org.apache.commons.statistics.distribution.WeibullDistribution
-
Support lower bound.
- survivalProbability(double) - Method in class org.apache.commons.statistics.distribution.BetaDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(double) - Method in class org.apache.commons.statistics.distribution.CauchyDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(double) - Method in class org.apache.commons.statistics.distribution.ChiSquaredDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(double) - Method in interface org.apache.commons.statistics.distribution.ContinuousDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(double) - Method in class org.apache.commons.statistics.distribution.ExponentialDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(double) - Method in class org.apache.commons.statistics.distribution.FDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(double) - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.HalfNormalDistribution
- survivalProbability(double) - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.RegularFoldedNormalDistribution
- survivalProbability(double) - Method in class org.apache.commons.statistics.distribution.GammaDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(double) - Method in class org.apache.commons.statistics.distribution.GumbelDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(double) - Method in class org.apache.commons.statistics.distribution.LaplaceDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(double) - Method in class org.apache.commons.statistics.distribution.LevyDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(double) - Method in class org.apache.commons.statistics.distribution.LogisticDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(double) - Method in class org.apache.commons.statistics.distribution.LogNormalDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(double) - Method in class org.apache.commons.statistics.distribution.LogUniformDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(double) - Method in class org.apache.commons.statistics.distribution.NakagamiDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(double) - Method in class org.apache.commons.statistics.distribution.NormalDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(double) - Method in class org.apache.commons.statistics.distribution.ParetoDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(double) - Method in class org.apache.commons.statistics.distribution.TDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(double) - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.DelegatedTrapezoidalDistribution
- survivalProbability(double) - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.RegularTrapezoidalDistribution
- survivalProbability(double) - Method in class org.apache.commons.statistics.distribution.TriangularDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(double) - Method in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(double) - Method in class org.apache.commons.statistics.distribution.UniformContinuousDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(double) - Method in class org.apache.commons.statistics.distribution.WeibullDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(int) - Method in class org.apache.commons.statistics.distribution.BinomialDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(int) - Method in interface org.apache.commons.statistics.distribution.DiscreteDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(int) - Method in class org.apache.commons.statistics.distribution.GeometricDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(int) - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(int) - Method in class org.apache.commons.statistics.distribution.PascalDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(int) - Method in class org.apache.commons.statistics.distribution.PoissonDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(int) - Method in class org.apache.commons.statistics.distribution.UniformDiscreteDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - survivalProbability(int) - Method in class org.apache.commons.statistics.distribution.ZipfDistribution
-
For a random variable
X
whose values are distributed according to this distribution, this method returnsP(X > x)
. - swap(int[], int, int) - Static method in class org.apache.commons.statistics.ranking.NaturalRanking.IntList
-
Swaps the two specified elements in the specified array.
T
- TDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of Student's t-distribution.
- TDistribution(double) - Constructor for class org.apache.commons.statistics.distribution.TDistribution
- TDistribution.NormalTDistribution - Class in org.apache.commons.statistics.distribution
-
Specialisation of the T-distribution used when there are infinite degrees of freedom.
- TDistribution.StudentsTDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of Student's T-distribution.
- test(double[]) - Method in class org.apache.commons.statistics.inference.TTest
-
Performs a one-sample t-test comparing the mean of the sample to
mu
. - test(double[]) - Method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Performs a Wilcoxon signed ranked statistic comparing the differences between sample values
z = x - y
tomu
. - test(double[], double[]) - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Performs a two-sample Kolmogorov-Smirnov test on samples
x
andy
. - test(double[], double[]) - Method in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
Performs a Mann-Whitney U test comparing the location for two independent samples.
- test(double[], double[]) - Method in class org.apache.commons.statistics.inference.TTest
-
Performs a two-sample t-test on independent samples comparing the difference in means of the samples to
mu
. - test(double[], double[]) - Method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Performs a Wilcoxon signed ranked statistic comparing mean for two related samples or repeated measurements on a single sample.
- test(double[], long[]) - Method in class org.apache.commons.statistics.inference.ChiSquareTest
-
Perform a chi-square goodness-of-fit test evaluating the null hypothesis that the
observed
counts conform to theexpected
counts. - test(double[], long[]) - Method in class org.apache.commons.statistics.inference.GTest
-
Perform a G-test for goodness-of-fit evaluating the null hypothesis that the
observed
counts conform to theexpected
counts. - test(double[], DoubleUnaryOperator) - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Performs a one-sample Kolmogorov-Smirnov test evaluating the null hypothesis that
x
conforms to the distribution cumulative density function (cdf
). - test(double, double, long) - Method in class org.apache.commons.statistics.inference.TTest
-
Perform a one-sample t-test comparing the mean of the dataset to
mu
. - test(double, double, long, double, double, long) - Method in class org.apache.commons.statistics.inference.TTest
-
Performs a two-sample t-test on independent samples comparing the difference in means of the datasets to
mu
. - test(int[][]) - Method in class org.apache.commons.statistics.inference.FisherExactTest
-
Performs Fisher's exact test on the 2-by-2 contingency table.
- test(int[][]) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Performs an unconditioned exact test on the 2-by-2 contingency table.
- test(int, int, double) - Method in class org.apache.commons.statistics.inference.BinomialTest
-
Performs a binomial test about the probability of success \( \pi \).
- test(long[]) - Method in class org.apache.commons.statistics.inference.ChiSquareTest
-
Perform a chi-square goodness-of-fit test evaluating the null hypothesis that the
observed
counts conform to a uniform distribution (each category is equally likely). - test(long[]) - Method in class org.apache.commons.statistics.inference.GTest
-
Perform a G-test for goodness-of-fit evaluating the null hypothesis that the
observed
counts conform to a uniform distribution (each category is equally likely). - test(long[][]) - Method in class org.apache.commons.statistics.inference.ChiSquareTest
-
Perform a chi-square test of independence based on the input
counts
array, viewed as a two-way table. - test(long[][]) - Method in class org.apache.commons.statistics.inference.GTest
-
Perform a G-test of independence based on the input
counts
array, viewed as a two-way table. - test(long[], long[]) - Method in class org.apache.commons.statistics.inference.ChiSquareTest
-
Perform a chi-square test of independence of frequency counts in
observed1
andobserved2
. - test(Collection<double[]>) - Method in class org.apache.commons.statistics.inference.OneWayAnova
-
Performs an ANOVA test for a collection of category data, evaluating the null hypothesis that there is no difference among the means of the data categories.
- testIntegralKolmogorovSmirnovStatistic(double[], double[], long, long) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Test if the two-sample integral Kolmogorov-Smirnov statistic is strictly greater than the specified values for D+ and D-.
- threshold - Variable in class org.apache.commons.statistics.inference.UnconditionedExactTest.Candidates
-
Current threshold for inclusion.
- tiedValues - Variable in class org.apache.commons.statistics.inference.MannWhitneyUTest.Result
-
Flag indicating the data has tied values.
- tiedValues - Variable in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest.Result
-
Flag indicating the data had tied values.
- tiesStrategy - Variable in class org.apache.commons.statistics.ranking.NaturalRanking
-
Ties strategy.
- TiesStrategy - Enum in org.apache.commons.statistics.ranking
-
Strategies for handling tied values in rank transformations.
- TiesStrategy() - Constructor for enum org.apache.commons.statistics.ranking.TiesStrategy
- toBigInteger() - Method in class org.apache.commons.statistics.descriptive.Int128
-
Convert to a BigInteger.
- toBigInteger() - Method in class org.apache.commons.statistics.descriptive.UInt128
-
Convert to a BigInteger.
- toBigInteger() - Method in class org.apache.commons.statistics.descriptive.UInt192
-
Convert to a BigInteger.
- toBigInteger() - Method in class org.apache.commons.statistics.descriptive.UInt96
-
Convert to a BigInteger.
- toBigIntegerExact(double) - Static method in class org.apache.commons.statistics.descriptive.IntMath
-
Return the whole number that is nearest to the
double
argumentx
as anint
, with ties rounding towards positive infinity. - toDD() - Method in class org.apache.commons.statistics.descriptive.Int128
-
Convert to a double-double.
- toDouble() - Method in class org.apache.commons.statistics.descriptive.Int128
-
Convert to a
double
. - toDouble() - Method in class org.apache.commons.statistics.descriptive.UInt128
-
Convert to a
double
. - toDouble() - Method in class org.apache.commons.statistics.descriptive.UInt192
-
Convert to a double.
- toIntExact() - Method in class org.apache.commons.statistics.descriptive.Int128
-
Convert to an
int
; throwing an exception if the value overflows anint
. - toIntExact() - Method in class org.apache.commons.statistics.descriptive.UInt128
-
Convert to an
int
; throwing an exception if the value overflows anint
. - toIntExact() - Method in class org.apache.commons.statistics.descriptive.UInt192
-
Convert to an
int
; throwing an exception if the value overflows anint
. - toIntExact(double) - Static method in class org.apache.commons.statistics.descriptive.IntMath
-
Return the whole number that is nearest to the
double
argumentx
as anint
, with ties rounding towards positive infinity. - toLongExact() - Method in class org.apache.commons.statistics.descriptive.Int128
-
Convert to a
long
; throwing an exception if the value overflows along
. - toLongExact() - Method in class org.apache.commons.statistics.descriptive.UInt128
-
Convert to a
long
; throwing an exception if the value overflows along
. - toLongExact() - Method in class org.apache.commons.statistics.descriptive.UInt192
-
Convert to a
long
; throwing an exception if the value overflows along
. - toLongExact(double) - Static method in class org.apache.commons.statistics.descriptive.IntMath
-
Return the whole number that is nearest to the
double
argumentx
as anlong
, with ties rounding towards positive infinity. - TOO_LARGE - Static variable in exception org.apache.commons.statistics.distribution.DistributionException
-
Error message for "too large" condition when
x > y
. - TOO_SMALL - Static variable in exception org.apache.commons.statistics.distribution.DistributionException
-
Error message for "too small" condition when
x < y
. - TrapezoidalDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the trapezoidal distribution.
- TrapezoidalDistribution(double, double, double, double) - Constructor for class org.apache.commons.statistics.distribution.TrapezoidalDistribution
- TrapezoidalDistribution.DelegatedTrapezoidalDistribution - Class in org.apache.commons.statistics.distribution
-
Specialisation of the trapezoidal distribution used when the distribution simplifies to an alternative distribution.
- TrapezoidalDistribution.RegularTrapezoidalDistribution - Class in org.apache.commons.statistics.distribution
-
Regular implementation of the trapezoidal distribution.
- TrapezoidalDistribution.TriangularTrapezoidalDistribution - Class in org.apache.commons.statistics.distribution
-
Specialisation of the trapezoidal distribution used when
b == c
. - TrapezoidalDistribution.UniformTrapezoidalDistribution - Class in org.apache.commons.statistics.distribution
-
Specialisation of the trapezoidal distribution used when
a == b
andc == d
. - TriangularDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the triangular distribution.
- TriangularDistribution(double, double, double) - Constructor for class org.apache.commons.statistics.distribution.TriangularDistribution
- TriangularTrapezoidalDistribution(double, double, double) - Constructor for class org.apache.commons.statistics.distribution.TrapezoidalDistribution.TriangularTrapezoidalDistribution
- TruncatedNormalDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the truncated normal distribution.
- TruncatedNormalDistribution(NormalDistribution, double, double, double) - Constructor for class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
- TTest - Class in org.apache.commons.statistics.inference
-
Implements Student's t-test statistics.
- TTest(AlternativeHypothesis, boolean, double) - Constructor for class org.apache.commons.statistics.inference.TTest
- TTest.Result - Class in org.apache.commons.statistics.inference
-
Result for the t-test.
- Two() - Constructor for class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
-
No instances.
- TWO - Static variable in class org.apache.commons.statistics.distribution.TDistribution.StudentsTDistribution
-
2.
- TWO - Static variable in class org.apache.commons.statistics.inference.Arguments
-
Two.
- TWO_CATEGORIES_REQUIRED - Static variable in exception org.apache.commons.statistics.inference.InferenceException
-
Error message for "categories
x < 2
". - TWO_PI - Static variable in class org.apache.commons.statistics.distribution.SaddlePointExpansionUtils
-
2 π.
- TWO_POW_53 - Static variable in class org.apache.commons.statistics.descriptive.IntMath
-
2^53.
- TWO_SIDED - org.apache.commons.statistics.inference.AlternativeHypothesis
-
Represents a two-sided test.
- TWO_VALUES_REQUIRED - Static variable in exception org.apache.commons.statistics.inference.InferenceException
-
Error message for "values
x < 2
". - TwoResult(double, int, double, boolean, double, double) - Constructor for class org.apache.commons.statistics.inference.KolmogorovSmirnovTest.TwoResult
-
Create an instance.
- twoSampleApproximateP(double, int, int, boolean) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Uses the Kolmogorov-Smirnov distribution to approximate \(P(D_{n,m} > d)\) where \(D_{n,m}\) is the 2-sample Kolmogorov-Smirnov statistic.
- twoSampleExactP(long, int, int, int, boolean, boolean) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Computes \(P(D_{n,m} > d)\) if
strict
istrue
; otherwise \(P(D_{n,m} \ge d)\), where \(D_{n,m}\) is the 2-sample Kolmogorov-Smirnov statistic, either the two-sided \(D_{n,m}\) or one-sided \(D_{n,m}^+\}. - twoSampleOneSidedPOutside(long, int, int, int) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Computes \(P(D_{n,m}^+ \ge d)\), where \(D_{n,m}^+\) is the 2-sample one-sided Kolmogorov-Smirnov statistic.
- twoSampleOneSidedPOutsideSquare(long, int) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Computes \(P(D_{n,n}^+ \ge d)\), where \(D_{n,n}^+\) is the 2-sample one-sided Kolmogorov-Smirnov statistic.
- twoSampleP(long, int, int, int, double, boolean) - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Computes \(P(D_{n,m} > d)\) for the 2-sample Kolmogorov-Smirnov statistic.
- twoSampleTwoSidedPOutsideSquare(long, int) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Computes \(P(D_{n,n}^+ \ge d)\), where \(D_{n,n}^+\) is the 2-sample two-sided Kolmogorov-Smirnov statistic.
- twoSampleTwoSidedPStabilizedInner(long, int, int, int) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Computes \(P(D_{n,m} \ge d)\), where \(D_{n,m}\) is the 2-sample Kolmogorov-Smirnov statistic.
- twoSidedBinomialTest(int, int, double, BinomialDistribution) - Static method in class org.apache.commons.statistics.inference.BinomialTest
-
Returns the observed significance level, or p-value, associated with a two-sided binomial test about the probability of success \( \pi \).
- twoSidedTest(int, HypergeometricDistribution) - Static method in class org.apache.commons.statistics.inference.FisherExactTest
-
Returns the observed significance level, or p-value, associated with a two-sided test about the observed value.
U
- UInt128 - Class in org.apache.commons.statistics.descriptive
-
A mutable 128-bit unsigned integer.
- UInt128() - Constructor for class org.apache.commons.statistics.descriptive.UInt128
-
Create an instance.
- UInt128(long, int, int) - Constructor for class org.apache.commons.statistics.descriptive.UInt128
-
Create an instance using a direct binary representation.
- UInt128(long, long) - Constructor for class org.apache.commons.statistics.descriptive.UInt128
-
Create an instance using a direct binary representation.
- uint128ToDouble(long, long) - Static method in class org.apache.commons.statistics.descriptive.IntMath
-
Convert an unsigned 128-bit integer to a
double
. - UInt192 - Class in org.apache.commons.statistics.descriptive
-
A mutable 192-bit unsigned integer.
- UInt192() - Constructor for class org.apache.commons.statistics.descriptive.UInt192
-
Create an instance.
- UInt192(long, int, int, int, int) - Constructor for class org.apache.commons.statistics.descriptive.UInt192
-
Create an instance using a direct binary representation.
- UInt192(long, long, long) - Constructor for class org.apache.commons.statistics.descriptive.UInt192
-
Create an instance using a direct binary representation.
- UInt96 - Class in org.apache.commons.statistics.descriptive
-
A mutable 96-bit unsigned integer.
- UInt96() - Constructor for class org.apache.commons.statistics.descriptive.UInt96
-
Create an instance.
- UInt96(long) - Constructor for class org.apache.commons.statistics.descriptive.UInt96
-
Create an instance.
- UInt96(long, int) - Constructor for class org.apache.commons.statistics.descriptive.UInt96
-
Create an instance using a direct binary representation.
- UnconditionedExactTest - Class in org.apache.commons.statistics.inference
-
Implements an unconditioned exact test for a contingency table.
- UnconditionedExactTest(AlternativeHypothesis, UnconditionedExactTest.Method, int, boolean) - Constructor for class org.apache.commons.statistics.inference.UnconditionedExactTest
- UnconditionedExactTest.BoschlooStatistic - Interface in org.apache.commons.statistics.inference
-
Compute the statistic for Boschloo's test.
- UnconditionedExactTest.Candidates - Class in org.apache.commons.statistics.inference
-
A container of (key,value) pairs to store candidate minima.
- UnconditionedExactTest.Method - Enum in org.apache.commons.statistics.inference
-
Define the method to determine the more extreme tables.
- UnconditionedExactTest.Result - Class in org.apache.commons.statistics.inference
-
Result for the unconditioned exact test.
- UnconditionedExactTest.XYList - Class in org.apache.commons.statistics.inference
-
An expandable list of (x,y) values.
- UniformContinuousDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the uniform distribution.
- UniformContinuousDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.UniformContinuousDistribution
- UniformDiscreteDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the uniform discrete distribution.
- UniformDiscreteDistribution(int, int) - Constructor for class org.apache.commons.statistics.distribution.UniformDiscreteDistribution
- UniformTrapezoidalDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.TrapezoidalDistribution.UniformTrapezoidalDistribution
- UNSET - Static variable in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
Value for an unset f computation.
- unsignedMultiply(int) - Method in class org.apache.commons.statistics.descriptive.UInt128
-
Multiply by the unsigned value.
- unsignedMultiply(int) - Method in class org.apache.commons.statistics.descriptive.UInt192
-
Multiply by the unsigned value.
- unsignedMultiplyHigh(long, long) - Static method in class org.apache.commons.statistics.descriptive.IntMath
-
Multiply the two values as if unsigned 64-bit longs to produce the high 64-bits of the 128-bit unsigned result.
- unsignedMultiplyToDouble(long, long) - Static method in class org.apache.commons.statistics.descriptive.IntMath
-
Multiply the arguments as if unsigned integers to a
double
result. - UNSUPPORTED_STATISTIC - Static variable in class org.apache.commons.statistics.descriptive.DoubleStatistics
-
Error message for an unsupported statistic.
- UNSUPPORTED_STATISTIC - Static variable in class org.apache.commons.statistics.descriptive.IntStatistics
-
Error message for an unsupported statistic.
- UNSUPPORTED_STATISTIC - Static variable in class org.apache.commons.statistics.descriptive.LongStatistics
-
Error message for an unsupported statistic.
- upper - Variable in class org.apache.commons.statistics.distribution.LogUniformDistribution
-
Upper bound (b) of this distribution (exclusive).
- upper - Variable in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
Upper bound of this distribution.
- upper - Variable in class org.apache.commons.statistics.distribution.UniformContinuousDistribution
-
Upper bound of this distribution (exclusive).
- upper - Variable in class org.apache.commons.statistics.distribution.UniformDiscreteDistribution
-
Upper bound (inclusive) of this distribution.
- upperBound - Variable in class org.apache.commons.statistics.distribution.HypergeometricDistribution
-
The upper bound of the support (inclusive).
- upperBound - Variable in class org.apache.commons.statistics.inference.Hypergeom
-
The upper bound of the support (inclusive).
- upperD - Variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest.TwoResult
-
Upper bound of the D statistic from all possible paths through regions with ties.
- upperMinusLower - Variable in class org.apache.commons.statistics.distribution.UniformContinuousDistribution
-
Range between the upper and lower bound of this distribution (cached for computations).
- upperMinusLowerPlus1 - Variable in class org.apache.commons.statistics.distribution.UniformDiscreteDistribution
-
"upper" - "lower" + 1 (as a double to avoid overflow).
- upperP - Variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest.TwoResult
-
The p-value of the upper D value.
V
- value - Variable in class org.apache.commons.statistics.inference.BrentOptimizer.PointValuePair
-
Value of the objective function at the point.
- value - Variable in class org.apache.commons.statistics.ranking.NaturalRanking.DataPosition
-
Data value.
- value(DoubleUnaryOperator, double) - Method in class org.apache.commons.statistics.inference.BracketFinder
-
Get the value of the function.
- value(Hypergeom, int) - Method in interface org.apache.commons.statistics.inference.UnconditionedExactTest.BoschlooStatistic
-
Compute Fisher's p-value for the 2x2 contingency table with the observed value
x
in position [0][0]. - valueOf(String) - Static method in enum org.apache.commons.statistics.descriptive.NaNPolicy
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.apache.commons.statistics.descriptive.Statistic
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.apache.commons.statistics.inference.AlternativeHypothesis
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.apache.commons.statistics.inference.ContinuityCorrection
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.apache.commons.statistics.inference.DataDispersion
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.apache.commons.statistics.inference.Inequality
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.apache.commons.statistics.inference.PValueMethod
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.apache.commons.statistics.inference.UnconditionedExactTest.Method
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.apache.commons.statistics.ranking.NaNStrategy
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.apache.commons.statistics.ranking.TiesStrategy
-
Returns the enum constant of this type with the specified name.
- values() - Static method in enum org.apache.commons.statistics.descriptive.NaNPolicy
-
Returns an array containing the constants of this enum type, in the order they are declared.
- values() - Static method in enum org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
-
Returns an array containing the constants of this enum type, in the order they are declared.
- values() - Static method in enum org.apache.commons.statistics.descriptive.Statistic
-
Returns an array containing the constants of this enum type, in the order they are declared.
- values() - Static method in enum org.apache.commons.statistics.inference.AlternativeHypothesis
-
Returns an array containing the constants of this enum type, in the order they are declared.
- values() - Static method in enum org.apache.commons.statistics.inference.ContinuityCorrection
-
Returns an array containing the constants of this enum type, in the order they are declared.
- values() - Static method in enum org.apache.commons.statistics.inference.DataDispersion
-
Returns an array containing the constants of this enum type, in the order they are declared.
- values() - Static method in enum org.apache.commons.statistics.inference.Inequality
-
Returns an array containing the constants of this enum type, in the order they are declared.
- values() - Static method in enum org.apache.commons.statistics.inference.PValueMethod
-
Returns an array containing the constants of this enum type, in the order they are declared.
- values() - Static method in enum org.apache.commons.statistics.inference.UnconditionedExactTest.Method
-
Returns an array containing the constants of this enum type, in the order they are declared.
- values() - Static method in enum org.apache.commons.statistics.ranking.NaNStrategy
-
Returns an array containing the constants of this enum type, in the order they are declared.
- values() - Static method in enum org.apache.commons.statistics.ranking.TiesStrategy
-
Returns an array containing the constants of this enum type, in the order they are declared.
- VALUES_MISMATCH - Static variable in exception org.apache.commons.statistics.inference.InferenceException
-
Error message for "mismatch" condition when "values x != y".
- VALUES_REQUIRED - Static variable in exception org.apache.commons.statistics.inference.InferenceException
-
Error message for "values
x < y
". - VAR - Static variable in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.HalfNormalDistribution
-
Variance constant (1 - 2/pi).
- variance - Variable in class org.apache.commons.statistics.distribution.BetaDistribution
-
Cached value for inverse probability function.
- variance - Variable in class org.apache.commons.statistics.distribution.FDistribution
-
Cached value for inverse probability function.
- variance - Variable in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.RegularFoldedNormalDistribution
-
Cached value for inverse probability function.
- variance - Variable in class org.apache.commons.statistics.distribution.GammaDistribution
-
Cached value for inverse probability function.
- variance - Variable in class org.apache.commons.statistics.distribution.NakagamiDistribution
-
Cached value for inverse probability function.
- variance - Variable in class org.apache.commons.statistics.distribution.TDistribution.StudentsTDistribution
-
Cached value for inverse probability function.
- variance(double, double) - Static method in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
-
Compute the variance of the truncated standard normal distribution.
- Variance - Class in org.apache.commons.statistics.descriptive
-
Computes the variance of the available values.
- Variance() - Constructor for class org.apache.commons.statistics.descriptive.Variance
-
Create an instance.
- Variance(SumOfSquaredDeviations) - Constructor for class org.apache.commons.statistics.descriptive.Variance
-
Creates an instance with the sum of squared deviations from the mean.
- VARIANCE - org.apache.commons.statistics.descriptive.Statistic
-
Variance.
- varianceDifference(double[], double[], double) - Static method in class org.apache.commons.statistics.inference.StatisticUtils
-
Returns the variance of the (signed) differences between corresponding elements of the input arrays, or
NaN
if the arrays are empty. - VERY_LARGE_N - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.One
-
"Very large" n to use a asymptotic limiting form.
W
- WeibullDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the Weibull distribution.
- WeibullDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.WeibullDistribution
- width - Variable in class org.apache.commons.statistics.inference.UnconditionedExactTest.XYList
-
Width, or maximum x value (exclusive).
- WilcoxonSignedRankTest - Class in org.apache.commons.statistics.inference
-
Implements the Wilcoxon signed-rank test.
- WilcoxonSignedRankTest(AlternativeHypothesis, PValueMethod, boolean, double) - Constructor for class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
- WilcoxonSignedRankTest.Result - Class in org.apache.commons.statistics.inference
-
Result for the Wilcoxon signed-rank test.
- with(UniformRandomProvider) - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Return an instance with the configured source of randomness.
- with(NaNPolicy) - Method in class org.apache.commons.statistics.descriptive.Median
-
Return an instance with the configured
NaNPolicy
. - with(NaNPolicy) - Method in class org.apache.commons.statistics.descriptive.Quantile
-
Return an instance with the configured
NaNPolicy
. - with(Quantile.EstimationMethod) - Method in class org.apache.commons.statistics.descriptive.Quantile
-
Return an instance with the configured
Quantile.EstimationMethod
. - with(AlternativeHypothesis) - Method in class org.apache.commons.statistics.inference.BinomialTest
-
Return an instance with the configured alternative hypothesis.
- with(AlternativeHypothesis) - Method in class org.apache.commons.statistics.inference.FisherExactTest
-
Return an instance with the configured alternative hypothesis.
- with(AlternativeHypothesis) - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Return an instance with the configured alternative hypothesis.
- with(AlternativeHypothesis) - Method in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
Return an instance with the configured alternative hypothesis.
- with(AlternativeHypothesis) - Method in class org.apache.commons.statistics.inference.TTest
-
Return an instance with the configured alternative hypothesis.
- with(AlternativeHypothesis) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Return an instance with the configured alternative hypothesis.
- with(AlternativeHypothesis) - Method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Return an instance with the configured alternative hypothesis.
- with(ContinuityCorrection) - Method in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
Return an instance with the configured continuity correction.
- with(ContinuityCorrection) - Method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Return an instance with the configured continuity correction.
- with(DataDispersion) - Method in class org.apache.commons.statistics.inference.TTest
-
Return an instance with the configured assumption on the data dispersion.
- with(Inequality) - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Return an instance with the configured inequality.
- with(PValueMethod) - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Return an instance with the configured p-value method.
- with(PValueMethod) - Method in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
Return an instance with the configured p-value method.
- with(PValueMethod) - Method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Return an instance with the configured p-value method.
- with(UnconditionedExactTest.Method) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Return an instance with the configured method.
- withBiased(boolean) - Method in class org.apache.commons.statistics.descriptive.StatisticsConfiguration
-
Return an instance with the configured biased option.
- withCopy(boolean) - Method in class org.apache.commons.statistics.descriptive.Median
-
Return an instance with the configured copy behaviour.
- withCopy(boolean) - Method in class org.apache.commons.statistics.descriptive.Quantile
-
Return an instance with the configured copy behaviour.
- withDefaults() - Static method in class org.apache.commons.statistics.descriptive.Median
-
Return a new instance with the default options.
- withDefaults() - Static method in class org.apache.commons.statistics.descriptive.Quantile
-
Return a new instance with the default options.
- withDefaults() - Static method in class org.apache.commons.statistics.descriptive.StatisticsConfiguration
-
Return an instance using the default options.
- withDefaults() - Static method in class org.apache.commons.statistics.inference.BinomialTest
-
Return an instance using the default options.
- withDefaults() - Static method in class org.apache.commons.statistics.inference.ChiSquareTest
-
Return an instance using the default options.
- withDefaults() - Static method in class org.apache.commons.statistics.inference.FisherExactTest
-
Return an instance using the default options.
- withDefaults() - Static method in class org.apache.commons.statistics.inference.GTest
-
Return an instance using the default options.
- withDefaults() - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Return an instance using the default options.
- withDefaults() - Static method in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
Return an instance using the default options.
- withDefaults() - Static method in class org.apache.commons.statistics.inference.OneWayAnova
-
Return an instance using the default options.
- withDefaults() - Static method in class org.apache.commons.statistics.inference.TTest
-
Return an instance using the default options.
- withDefaults() - Static method in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Return an instance using the default options.
- withDefaults() - Static method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Return an instance using the default options.
- withDegreesOfFreedomAdjustment(int) - Method in class org.apache.commons.statistics.inference.ChiSquareTest
-
Return an instance with the configured degrees of freedom adjustment.
- withDegreesOfFreedomAdjustment(int) - Method in class org.apache.commons.statistics.inference.GTest
-
Return an instance with the configured degrees of freedom adjustment.
- withInitialPoints(int) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Return an instance with the configured number of initial points.
- withIterations(int) - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
-
Return an instance with the configured number of iterations.
- withMu(double) - Method in class org.apache.commons.statistics.inference.MannWhitneyUTest
-
Return an instance with the configured location shift
mu
. - withMu(double) - Method in class org.apache.commons.statistics.inference.TTest
-
Return an instance with the configured
mu
. - withMu(double) - Method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
-
Return an instance with the configured expected difference
mu
. - withOptimize(boolean) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest
-
Return an instance with the configured optimization of initial search points.
X
- X_GT_Y - Static variable in exception org.apache.commons.statistics.inference.InferenceException
-
Error message for "too large" condition when "
x > y
". - X_GTE_Y - Static variable in exception org.apache.commons.statistics.inference.InferenceException
-
Error message for "too large" condition when "
x >= y
". - X_KS_HALF - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution
-
Value of x when the KS sum is 0.5.
- X_KS_ONE - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution
-
Value of x when the KS sum is 1.0.
- X_LT_Y - Static variable in exception org.apache.commons.statistics.inference.InferenceException
-
Error message for "too small" condition when "
x < y
". - xsqrt2pi(double) - Static method in class org.apache.commons.statistics.distribution.ExtendedPrecision
-
Multiply the term by sqrt(2 pi).
- XYList(int, int) - Constructor for class org.apache.commons.statistics.inference.UnconditionedExactTest.XYList
-
Create an instance.
Z
- Z_POOLED - org.apache.commons.statistics.inference.UnconditionedExactTest.Method
-
Uses the test statistic from a Z-test using a pooled variance.
- Z_UNPOOLED - org.apache.commons.statistics.inference.UnconditionedExactTest.Method
-
Uses the test statistic from a Z-test using an unpooled variance.
- ZERO - Static variable in exception org.apache.commons.statistics.inference.InferenceException
-
Error message for "zero" condition when "
x == 0
". - ZERO_AT - Static variable in exception org.apache.commons.statistics.inference.InferenceException
-
Error message for "zero" condition when "
x[i] == 0
". - zeroValues - Variable in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest.Result
-
Flag indicating the data had zero values.
- zeroVariance(double, double) - Static method in class org.apache.commons.statistics.descriptive.Statistics
-
Returns
true
if the second central momentm2
is effectively zero given the magnitude of the first raw momentm1
. - ZipfDistribution - Class in org.apache.commons.statistics.distribution
-
Implementation of the Zipf distribution.
- ZipfDistribution(int, double) - Constructor for class org.apache.commons.statistics.distribution.ZipfDistribution
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