Index

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 and Interfaces|All Packages|Constant Field Values

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 the statistic.
add(T, int[]) - Static method in class org.apache.commons.statistics.descriptive.Statistics
Add all the values to the statistic.
add(T, long[]) - Static method in class org.apache.commons.statistics.descriptive.Statistics
Add all the values to the statistic.
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 to nanStrategy and ties resolved using tiesStrategy.
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 - Enum constant in enum org.apache.commons.statistics.inference.PValueMethod
Use the asymptotic distribution of the test statistic to evaluate the p-value.
AUTO - Enum constant in enum 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 - Enum constant in enum 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 - Enum constant in enum 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 the other 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 approximation x 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 input values.
build(int...) - Method in class org.apache.commons.statistics.descriptive.IntStatistics.Builder
Builds a IntStatistics instance using the input values.
build(long...) - Method in class org.apache.commons.statistics.descriptive.LongStatistics.Builder
Builds a LongStatistics instance using the input values.
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 class 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 is null or else the right-hand side argument b must be run-time assignable to the same class as a 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 is null or else the right-hand side argument b 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 argument b.
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 argument b.
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 composite IntConsumer.
composeAsLong(DoubleConsumer...) - Static method in class org.apache.commons.statistics.descriptive.LongStatistics
Chain the consumers into a single composite LongConsumer.
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 to mu.
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 to mu.
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 and s.
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 size m 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
Creates a NaNTransformer based on the nanPolicy and data copy policy.
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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 - Enum constant in enum 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 Class in org.apache.commons.statistics.distribution
Package private exception class with constants for frequently used messages.
DistributionException(String, Object...) - Constructor for exception class 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 count n.
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 - Enum constant in enum 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 - Enum constant in enum org.apache.commons.statistics.descriptive.NaNPolicy
NaNs result in an exception.
ErrorNaNTransformer(boolean) - Constructor for class org.apache.commons.statistics.descriptive.NaNTransformers.ErrorNaNTransformer
 
ESTIMATE - Enum constant in enum 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 and y 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 - Enum constant in enum 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 - Enum constant in enum 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 assuming a+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 - Enum constant in enum 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 in tiesTrace.
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 - Enum constant in enum 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 - Enum constant in enum 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 a BigInteger.
getAsBigInteger(Statistic) - Method in class org.apache.commons.statistics.descriptive.LongStatistics
Gets the value of the specified statistic as a BigInteger.
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 a double.
getAsDouble(Statistic) - Method in class org.apache.commons.statistics.descriptive.IntStatistics
Gets the value of the specified statistic as a double.
getAsDouble(Statistic) - Method in class org.apache.commons.statistics.descriptive.LongStatistics
Gets the value of the specified statistic as a double.
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 an int.
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 a long.
getAsLong(Statistic) - Method in class org.apache.commons.statistics.descriptive.LongStatistics
Gets the value of the specified statistic as a long.
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 the other 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 the other 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 - Enum constant in enum 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 - Enum constant in enum org.apache.commons.statistics.inference.DataDispersion
Data does not have the same variance.
HF1 - Enum constant in enum org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
Inverse of the empirical distribution function.
HF2 - Enum constant in enum org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
Similar to Quantile.EstimationMethod.HF1 with averaging at discontinuities.
HF3 - Enum constant in enum org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
The observation closest to \( np \).
HF4 - Enum constant in enum org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
Linear interpolation of the inverse of the empirical CDF.
HF5 - Enum constant in enum 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 - Enum constant in enum org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
Linear interpolation of the expectations for the order statistics for the uniform distribution on [0,1].
HF7 - Enum constant in enum org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
Linear interpolation of the modes for the order statistics for the uniform distribution on [0,1].
HF8 - Enum constant in enum org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
Linear interpolation of the approximate medians for order statistics.
HF9 - Enum constant in enum 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 - Enum constant in enum 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 - Enum constant in enum 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 part g 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 Class in org.apache.commons.statistics.inference
Package private exception class with constants for frequently used messages.
InferenceException(String) - Constructor for exception class org.apache.commons.statistics.inference.InferenceException
Creates an exception.
InferenceException(String, Object...) - Constructor for exception class 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 returns P(x0 <= X <= x1).
innerCumulativeProbability(int, int) - Method in class org.apache.commons.statistics.inference.Hypergeom
For this distribution, X, this method returns P(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 interpolant t 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 class 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 class org.apache.commons.statistics.distribution.DistributionException
Error message for "invalid probability" condition when "x not in [0, 1]".
INVALID_PROBABILITY - Static variable in exception class 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 class org.apache.commons.statistics.distribution.DistributionException
Error message for "invalid range" condition when "lower > upper".
INVALID_RANGE_LOW_GTE_HIGH - Static variable in exception class org.apache.commons.statistics.distribution.DistributionException
Error message for "invalid range" condition when "lower >= upper".
INVALID_SIGNIFICANCE - Static variable in exception class 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 - Enum constant in enum 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 - Enum constant in enum 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), where p 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 returns log(P(X = x)), where log 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 returns log(P(X = x)), where log 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 returns log(P(X = x)), where log 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 returns log(P(X = x)), where log 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 returns log(P(X = x)), where log 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 returns log(P(X = x)), where log 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 returns log(P(X = x)), where log 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 returns log(P(X = x)), where log 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, where p is the probability of success and n 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 - Enum constant in enum 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 - Enum constant in enum 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 - Enum constant in enum 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 - Enum constant in enum 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 - Enum constant in enum 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 - Enum constant in enum 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 - Enum constant in enum 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 by b.
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 NaNStrategy.FAILED and AVERAGE.
NaturalRanking(IntUnaryOperator) - Constructor for class org.apache.commons.statistics.ranking.NaturalRanking
Creates an instance with NaNStrategy.FAILED, 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 and AVERAGE.
NaturalRanking(NaNStrategy, IntUnaryOperator) - Constructor for class org.apache.commons.statistics.ranking.NaturalRanking
Creates an instance with the specified @nanStrategy, 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 NaNStrategy.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 class org.apache.commons.statistics.distribution.DistributionException
Error message for "negative" condition when x < 0.
NEGATIVE - Static variable in exception class 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 class 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 - Enum constant in enum 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 class 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 class org.apache.commons.statistics.distribution.DistributionException
Error message for "not strictly positive" condition when x <= 0.
NOT_STRICTLY_POSITIVE - Static variable in exception class org.apache.commons.statistics.inference.InferenceException
Error message for "not strictly positive" condition when "x <= 0".
NOT_STRICTLY_POSITIVE_FINITE - Static variable in exception class 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 input values.
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 input values.
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 input values.
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 class 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 power n.
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 itself n 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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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, where p is the probability of success and n 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 - Enum constant in enum 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 - Enum constant in enum 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 - Enum constant in enum 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 of double sample values.
samples(long) - Method in interface org.apache.commons.statistics.distribution.DiscreteDistribution.Sampler
Returns a stream producing the given streamSize number of int 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 and b inclusive to find the highest index where value <= x.
searchDescending(int, int, double, IntToDoubleFunction) - Static method in class org.apache.commons.statistics.inference.Searches
Conduct a search between a inclusive and b inclusive to find the lowest index where value <= 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 - Enum constant in enum org.apache.commons.statistics.ranking.TiesStrategy
Ties are assigned ranks in order of occurrence in the original array.
serialVersionUID - Static variable in exception class org.apache.commons.statistics.distribution.DistributionException
Serializable version identifier.
serialVersionUID - Static variable in exception class 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 - Enum constant in enum 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
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 with k an integer and alpha 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 a double[] 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 - Enum constant in enum 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 to mu.
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 and expected frequency counts.
statistic(double[], long[]) - Method in class org.apache.commons.statistics.inference.GTest
Computes the G-test goodness-of-fit statistic comparing observed and expected 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 and observed2.
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> - 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 - Enum constant in enum 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 - Enum constant in enum org.apache.commons.statistics.descriptive.Statistic
Sum.
SUM_OF_LOGS - Enum constant in enum org.apache.commons.statistics.descriptive.Statistic
Sum of the natural logarithm of values.
SUM_OF_SQUARES - Enum constant in enum 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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 returns P(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 to mu.
test(double[], double[]) - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
Performs a two-sample Kolmogorov-Smirnov test on samples x and y.
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 the expected 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 the expected 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 and observed2.
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 argument x as an int, 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 an int.
toIntExact() - Method in class org.apache.commons.statistics.descriptive.UInt128
Convert to an int; throwing an exception if the value overflows an int.
toIntExact() - Method in class org.apache.commons.statistics.descriptive.UInt192
Convert to an int; throwing an exception if the value overflows an int.
toIntExact(double) - Static method in class org.apache.commons.statistics.descriptive.IntMath
Return the whole number that is nearest to the double argument x as an int, 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 a long.
toLongExact() - Method in class org.apache.commons.statistics.descriptive.UInt128
Convert to a long; throwing an exception if the value overflows a long.
toLongExact() - Method in class org.apache.commons.statistics.descriptive.UInt192
Convert to a long; throwing an exception if the value overflows a long.
toLongExact(double) - Static method in class org.apache.commons.statistics.descriptive.IntMath
Return the whole number that is nearest to the double argument x as an long, with ties rounding towards positive infinity.
TOO_LARGE - Static variable in exception class org.apache.commons.statistics.distribution.DistributionException
Error message for "too large" condition when x > y.
TOO_SMALL - Static variable in exception class 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 and c == 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 class 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 - Enum constant in enum org.apache.commons.statistics.inference.AlternativeHypothesis
Represents a two-sided test.
TWO_VALUES_REQUIRED - Static variable in exception class 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 is true; 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 class org.apache.commons.statistics.inference.InferenceException
Error message for "mismatch" condition when "values x != y".
VALUES_REQUIRED - Static variable in exception class 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 - Enum constant in enum 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 class org.apache.commons.statistics.inference.InferenceException
Error message for "too large" condition when "x > y".
X_GTE_Y - Static variable in exception class 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 class 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 - Enum constant in enum org.apache.commons.statistics.inference.UnconditionedExactTest.Method
Uses the test statistic from a Z-test using a pooled variance.
Z_UNPOOLED - Enum constant in enum org.apache.commons.statistics.inference.UnconditionedExactTest.Method
Uses the test statistic from a Z-test using an unpooled variance.
ZERO - Static variable in exception class org.apache.commons.statistics.inference.InferenceException
Error message for "zero" condition when "x == 0".
ZERO_AT - Static variable in exception class 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 moment m2 is effectively zero given the magnitude of the first raw moment m1.
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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