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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 - org.apache.commons.statistics.inference.PValueMethod
Use the asymptotic distribution of the test statistic to evaluate the p-value.
AUTO - org.apache.commons.statistics.inference.PValueMethod
Automatically choose the method to evaluate the p-value.
AUTO_LIMIT - Static variable in class org.apache.commons.statistics.inference.MannWhitneyUTest
Limit on sample size for the exact p-value computation for the auto mode.
AUTO_LIMIT - Static variable in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
Limit on sample size for the exact p-value computation for the auto mode.
AVERAGE - org.apache.commons.statistics.ranking.TiesStrategy
Tied values are assigned the average of the applicable ranks.

B

b - Variable in class org.apache.commons.statistics.distribution.TrapezoidalDistribution
Start of the trapezoid constant density.
b - Variable in class org.apache.commons.statistics.distribution.TriangularDistribution
Upper limit of this distribution (inclusive).
BaseSignificanceResult - Class in org.apache.commons.statistics.inference
Base implementation for the result of a test for significance.
BaseSignificanceResult(double, double) - Constructor for class org.apache.commons.statistics.inference.BaseSignificanceResult
Create an instance.
beta - Variable in class org.apache.commons.statistics.distribution.BetaDistribution
Second shape parameter.
beta - Variable in class org.apache.commons.statistics.distribution.GumbelDistribution
Scale parameter.
beta - Variable in class org.apache.commons.statistics.distribution.LaplaceDistribution
The scale parameter.
BetaDistribution - Class in org.apache.commons.statistics.distribution
Implementation of the beta distribution.
BetaDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.BetaDistribution
 
biased - Variable in class org.apache.commons.statistics.descriptive.IntStandardDeviation
Flag to control if the statistic is biased, or should use a bias correction.
biased - Variable in class org.apache.commons.statistics.descriptive.IntVariance
Flag to control if the statistic is biased, or should use a bias correction.
biased - Variable in class org.apache.commons.statistics.descriptive.Kurtosis
Flag to control if the statistic is biased, or should use a bias correction.
biased - Variable in class org.apache.commons.statistics.descriptive.LongStandardDeviation
Flag to control if the statistic is biased, or should use a bias correction.
biased - Variable in class org.apache.commons.statistics.descriptive.LongVariance
Flag to control if the statistic is biased, or should use a bias correction.
biased - Variable in class org.apache.commons.statistics.descriptive.Skewness
Flag to control if the statistic is biased, or should use a bias correction.
biased - Variable in class org.apache.commons.statistics.descriptive.StandardDeviation
Flag to control if the statistic is biased, or should use a bias correction.
biased - Variable in class org.apache.commons.statistics.descriptive.StatisticsConfiguration
Flag to control if the statistic is biased, or should use a bias correction.
biased - Variable in class org.apache.commons.statistics.descriptive.Variance
Flag to control if the statistic is biased, or should use a bias correction.
BIG - Static variable in class org.apache.commons.statistics.distribution.ExtendedPrecision
Threshold for a big number that may overflow when squared.
BigIntegerStatisticResult - Interface in org.apache.commons.statistics.descriptive
Represents the BigInteger result of a statistic computed over a set of values.
BINARY_SEARCH - Static variable in class org.apache.commons.statistics.inference.Searches
Range threshold to use a binary search.
binom(int, int) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
Compute the binomial coefficient binom(n, k).
BinomialDistribution - Class in org.apache.commons.statistics.distribution
Implementation of the binomial distribution.
BinomialDistribution(int, double) - Constructor for class org.apache.commons.statistics.distribution.BinomialDistribution
 
BinomialTest - Class in org.apache.commons.statistics.inference
Implements binomial test statistics.
BinomialTest(AlternativeHypothesis) - Constructor for class org.apache.commons.statistics.inference.BinomialTest
 
bma - Variable in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.RegularTrapezoidalDistribution
Cached value (b - a).
BOSCHLOO - org.apache.commons.statistics.inference.UnconditionedExactTest.Method
Uses the p-value from Fisher's exact test.
bp - Variable in class org.apache.commons.statistics.distribution.HypergeometricDistribution
Binomial probability of success (sampleSize / populationSize).
bq - Variable in class org.apache.commons.statistics.distribution.HypergeometricDistribution
Binomial probability of failure ((populationSize - sampleSize) / populationSize).
BracketFinder - Class in org.apache.commons.statistics.inference
Provide an interval that brackets a local minimum of a function.
BracketFinder() - Constructor for class org.apache.commons.statistics.inference.BracketFinder
Constructor with default values 100, 100000 (see 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 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 - org.apache.commons.statistics.inference.ContinuityCorrection
Disable continuity correction.
DiscreteDistribution - Interface in org.apache.commons.statistics.distribution
Interface for distributions on the integers.
DiscreteDistribution.Sampler - Interface in org.apache.commons.statistics.distribution
Distribution sampling functionality.
DistributionException - Exception in org.apache.commons.statistics.distribution
Package private exception class with constants for frequently used messages.
DistributionException(String, Object...) - Constructor for exception org.apache.commons.statistics.distribution.DistributionException
Creates an exception.
divide(Int128, long) - Static method in class org.apache.commons.statistics.descriptive.IntMath
Divide value x by the 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 - org.apache.commons.statistics.inference.ContinuityCorrection
Enable continuity correction.
eps - Variable in class org.apache.commons.statistics.inference.UnconditionedExactTest.Candidates
Relative distance from lowest candidate.
EPS - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution
Machine epsilon, 2^-52.
EPS_MIN - Static variable in class org.apache.commons.statistics.inference.BracketFinder
Tolerance to avoid division by zero.
equalVariances - Variable in class org.apache.commons.statistics.inference.TTest
Assume the two samples have the same population variance.
ERROR - org.apache.commons.statistics.descriptive.NaNPolicy
NaNs result in an exception.
ErrorNaNTransformer(boolean) - Constructor for class org.apache.commons.statistics.descriptive.NaNTransformers.ErrorNaNTransformer
 
ESTIMATE - org.apache.commons.statistics.inference.PValueMethod
Use an estimation method for the p-value.
estimateP(double[], double[], long) - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
Estimates the p-value of a two-sample Kolmogorov-Smirnov test evaluating the null hypothesis that x 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 - org.apache.commons.statistics.inference.PValueMethod
Use the exact distribution of the test statistic to evaluate the p-value.
EXACT_LIMIT - Static variable in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
Limit on sample size for the exact p-value computation.
EXACT_STIRLING_ERRORS - Static variable in class org.apache.commons.statistics.distribution.SaddlePointExpansionUtils
Exact Stirling expansion error for certain values.
EXCLUDE - org.apache.commons.statistics.descriptive.NaNPolicy
NaNs are excluded from the data.
ExcludeNaNTransformer(boolean) - Constructor for class org.apache.commons.statistics.descriptive.NaNTransformers.ExcludeNaNTransformer
 
exp - Variable in class org.apache.commons.statistics.inference.SquareMatrixSupport.ArrayRealSquareMatrix
Matrix scale.
EXP_BIAS - Static variable in class org.apache.commons.statistics.descriptive.IntMath
Bias offset for the exponent of a double.
EXP_M_HALF_XX_MAX_VALUE - Static variable in class org.apache.commons.statistics.distribution.ExtendedPrecision
Approximate x squared value where exp(-0.5*x*x) == 0.
EXP_M_HALF_XX_MIN_VALUE - Static variable in class org.apache.commons.statistics.distribution.ExtendedPrecision
X squared value where exp(-0.5*x*x) cannot increase accuracy using the round-off from x squared.
EXP_SHIFT - Static variable in class org.apache.commons.statistics.descriptive.IntMath
Shift for the exponent of a double.
expmhxx(double) - Static method in class org.apache.commons.statistics.distribution.ExtendedPrecision
Compute exp(-0.5*x*x) with high accuracy.
exponent - Variable in class org.apache.commons.statistics.distribution.ZipfDistribution
Exponent parameter of the distribution.
ExponentialDistribution - Class in org.apache.commons.statistics.distribution
Implementation of the exponential distribution.
ExponentialDistribution(double) - Constructor for class org.apache.commons.statistics.distribution.ExponentialDistribution
 
expxx(double, double) - Static method in class org.apache.commons.statistics.distribution.ExtendedPrecision
Compute exp(a+b) with high accuracy 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 - 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 - org.apache.commons.statistics.ranking.NaNStrategy
NaNs are left fixed "in place", that is the rank transformation is applied to the other elements in the input array, but the NaN elements are returned unchanged.
fLo - Variable in class org.apache.commons.statistics.inference.BracketFinder
Function value at BracketFinder.lo.
fMid - Variable in class org.apache.commons.statistics.inference.BracketFinder
Function value at BracketFinder.mid.
fmnk(double[][][], int, int, int) - Static method in class org.apache.commons.statistics.inference.MannWhitneyUTest
Compute f(m; n; k), the number of subsets of {0; 1; ...; n} with m elements such that the elements of this subset add up to k.
FoldedNormalDistribution - Class in org.apache.commons.statistics.distribution
Implementation of the folded normal distribution.
FoldedNormalDistribution(double) - Constructor for class org.apache.commons.statistics.distribution.FoldedNormalDistribution
 
FoldedNormalDistribution.HalfNormalDistribution - Class in org.apache.commons.statistics.distribution
Specialisation for the half-normal distribution.
FoldedNormalDistribution.RegularFoldedNormalDistribution - Class in org.apache.commons.statistics.distribution
Regular implementation of the folded normal distribution.
forEach(Consumer<double[]>) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest.Candidates
Perform the given action for each (key, value) pair.
FOUR_A - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
Factor 4a in the quadratic equation to solve max k: log(2^-52) * 8.

G

gamma - Variable in class org.apache.commons.statistics.distribution.ChiSquaredDistribution
Internal Gamma distribution.
GammaDistribution - Class in org.apache.commons.statistics.distribution
Implementation of the gamma distribution.
GammaDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.GammaDistribution
 
generalizedHarmonic(int, double) - Static method in class org.apache.commons.statistics.distribution.ZipfDistribution
Calculates the Nth generalized harmonic number.
generalizedHarmonicAscendingSum(int, double) - Static method in class org.apache.commons.statistics.distribution.ZipfDistribution
Calculates the Nth generalized harmonic number.
GEOMETRIC_MEAN - org.apache.commons.statistics.descriptive.Statistic
Geometric mean.
GeometricDistribution - Class in org.apache.commons.statistics.distribution
Implementation of the geometric distribution.
GeometricDistribution(double) - Constructor for class org.apache.commons.statistics.distribution.GeometricDistribution
 
GeometricMean - Class in org.apache.commons.statistics.descriptive
Computes the geometric mean of the available values.
GeometricMean() - Constructor for class org.apache.commons.statistics.descriptive.GeometricMean
Create an instance.
GeometricMean(SumOfLogs, long) - Constructor for class org.apache.commons.statistics.descriptive.GeometricMean
Create an instance.
get(int) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest.XYList
Gets the 2D index at the specified index.
get(int) - Method in class org.apache.commons.statistics.ranking.NaturalRanking.IntList
Gets the element at the specified index.
get(int, int) - Method in class org.apache.commons.statistics.inference.SquareMatrixSupport.ArrayRealSquareMatrix
 
get(int, int) - Method in interface org.apache.commons.statistics.inference.SquareMatrixSupport.RealSquareMatrix
Gets the value.
getAlpha() - Method in class org.apache.commons.statistics.distribution.BetaDistribution
Gets the first shape parameter of this distribution.
getAsBigInteger() - Method in interface org.apache.commons.statistics.descriptive.BigIntegerStatisticResult
 
getAsBigInteger() - Method in class org.apache.commons.statistics.descriptive.IntMax
 
getAsBigInteger() - Method in class org.apache.commons.statistics.descriptive.IntMin
 
getAsBigInteger() - Method in interface org.apache.commons.statistics.descriptive.IntStatisticResult
 
getAsBigInteger() - Method in class org.apache.commons.statistics.descriptive.IntSum
Gets the sum of all input values.
getAsBigInteger() - Method in class org.apache.commons.statistics.descriptive.IntSumOfSquares
Gets the sum of squares of all input values.
getAsBigInteger() - Method in class org.apache.commons.statistics.descriptive.LongMax
 
getAsBigInteger() - Method in class org.apache.commons.statistics.descriptive.LongMin
 
getAsBigInteger() - Method in interface org.apache.commons.statistics.descriptive.LongStatisticResult
 
getAsBigInteger() - Method in class org.apache.commons.statistics.descriptive.LongSum
Gets the sum of all input values.
getAsBigInteger() - Method in class org.apache.commons.statistics.descriptive.LongSumOfSquares
Gets the sum of squares of all input values.
getAsBigInteger() - Method in interface org.apache.commons.statistics.descriptive.StatisticResult
Gets a result as a BigInteger.
getAsBigInteger(Statistic) - Method in class org.apache.commons.statistics.descriptive.IntStatistics
Gets the value of the specified statistic as 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 - org.apache.commons.statistics.inference.AlternativeHypothesis
Represents a right-sided test.
growLimit - Variable in class org.apache.commons.statistics.inference.BracketFinder
Factor for expanding the interval.
GTest - Class in org.apache.commons.statistics.inference
Implements G-test (Generalized Log-Likelihood Ratio Test) statistics.
GTest(int) - Constructor for class org.apache.commons.statistics.inference.GTest
 
GumbelDistribution - Class in org.apache.commons.statistics.distribution
Implementation of the Gumbel distribution.
GumbelDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.GumbelDistribution
 

H

HALF - Static variable in class org.apache.commons.statistics.descriptive.IntMath
0.5.
HALF - Static variable in class org.apache.commons.statistics.distribution.BinomialDistribution
1/2.
HALF - Static variable in class org.apache.commons.statistics.distribution.GeometricDistribution
1/2.
HALF - Static variable in class org.apache.commons.statistics.distribution.HypergeometricDistribution
1/2.
HALF - Static variable in class org.apache.commons.statistics.inference.Hypergeom
1/2.
HALF - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
1/2.
HALF_LOG_TWO_PI - Static variable in class org.apache.commons.statistics.distribution.Constants
0.5 * ln(2 pi).
HALF_OVER_ERFCINV_HALF_SQUARED - Static variable in class org.apache.commons.statistics.distribution.LevyDistribution
1 / 2(erfc^-1 (0.5))^2.
halfC - Variable in class org.apache.commons.statistics.distribution.LevyDistribution
Half of c (for calculations).
HalfNormalDistribution(double) - Constructor for class org.apache.commons.statistics.distribution.FoldedNormalDistribution.HalfNormalDistribution
 
hasSignificantTies() - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest.TwoResult
Returns true if there were ties between samples that occurred in a region which could change the D statistic if the ties were resolved to a defined order.
hasTiedValues() - Method in class org.apache.commons.statistics.inference.MannWhitneyUTest.Result
Return true if the data had tied values.
hasTiedValues() - Method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest.Result
Return true if the data had tied values (with equal ranks).
hasZeroValues() - Method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest.Result
Return true if the data had zero values.
HETEROSCEDASTIC - org.apache.commons.statistics.inference.DataDispersion
Data does not have the same variance.
HF1 - org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
Inverse of the empirical distribution function.
HF2 - org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
Similar to Quantile.EstimationMethod.HF1 with averaging at discontinuities.
HF3 - org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
The observation closest to \( np \).
HF4 - org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
Linear interpolation of the inverse of the empirical CDF.
HF5 - org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
A piecewise linear function where the knots are the values midway through the steps of the empirical CDF.
HF6 - org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
Linear interpolation of the expectations for the order statistics for the uniform distribution on [0,1].
HF7 - org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
Linear interpolation of the modes for the order statistics for the uniform distribution on [0,1].
HF8 - org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
Linear interpolation of the approximate medians for order statistics.
HF9 - org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
Quantile estimates are approximately unbiased for the expected order statistics if \( x \) is normally distributed.
hi - Variable in class org.apache.commons.statistics.descriptive.Int128
high 64-bits.
hi - Variable in class org.apache.commons.statistics.inference.BracketFinder
Higher bound of the bracket.
hi64() - Method in class org.apache.commons.statistics.descriptive.Int128
Return the higher 64-bits as a long value.
hi64() - Method in class org.apache.commons.statistics.descriptive.UInt128
Return the higher 64-bits as a long value.
hi64() - Method in class org.apache.commons.statistics.descriptive.UInt192
Return the higher 64-bits as a long value.
hi64() - Method in class org.apache.commons.statistics.descriptive.UInt96
Return the higher 64-bits as a long value.
HOMOSCEDASTIC - org.apache.commons.statistics.inference.DataDispersion
All data has the same finite variance (homogeneity of variance).
Hypergeom - Class in org.apache.commons.statistics.inference
Provide a wrapper around the HypergeometricDistribution that caches all probability mass values.
Hypergeom(int, int, int) - Constructor for class org.apache.commons.statistics.inference.Hypergeom
 
HypergeometricDistribution - Class in org.apache.commons.statistics.distribution
Implementation of the hypergeometric distribution.
HypergeometricDistribution(int, int, int) - Constructor for class org.apache.commons.statistics.distribution.HypergeometricDistribution
 

I

identity() - Method in class org.apache.commons.statistics.inference.SquareMatrixSupport.ArrayRealSquareMatrix
Creates the identity matrix I with the same dimension as this.
IGNORED_D - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
Placeholder to use for the two-sample ties D array when the value can be ignored.
IGNORED_SIGN - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
Placeholder to use for the two-sample sign array when the value can be ignored.
INC_FRACTION - Static variable in class org.apache.commons.statistics.inference.UnconditionedExactTest
Fraction of the increment (interval between enumerated points) to initialise the bracket for the minima.
INCLUDE - org.apache.commons.statistics.descriptive.NaNPolicy
NaNs are included in the data.
IncludeNaNTransformer(boolean) - Constructor for class org.apache.commons.statistics.descriptive.NaNTransformers.IncludeNaNTransformer
 
INCOMPATIBLE_STATISTICS - Static variable in class org.apache.commons.statistics.descriptive.Statistics
Error message for an incompatible statistics.
index(double, int) - Method in enum org.apache.commons.statistics.descriptive.Quantile.EstimationMethod
Finds the index i and fractional 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 in org.apache.commons.statistics.inference
Package private exception class with constants for frequently used messages.
InferenceException(String) - Constructor for exception org.apache.commons.statistics.inference.InferenceException
Creates an exception.
InferenceException(String, Object...) - Constructor for exception org.apache.commons.statistics.inference.InferenceException
Creates an exception.
initialize(double[]) - Static method in class org.apache.commons.statistics.inference.MannWhitneyUTest
Initialize the array for f(m, n, x).
innerCumulativeProbability(int, int) - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
For this distribution, X, this method 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 org.apache.commons.statistics.distribution.DistributionException
Error message for "invalid non-zero probability" condition when "x not in (0, 1]".
INVALID_NUMBER_OF_PROBABILITIES - Static variable in class org.apache.commons.statistics.descriptive.Quantile
Message when the number of probabilities in a range is not valid.
INVALID_PROBABILITY - Static variable in class org.apache.commons.statistics.descriptive.Quantile
Message when the probability is not in the range [0, 1].
INVALID_PROBABILITY - Static variable in exception org.apache.commons.statistics.distribution.DistributionException
Error message for "invalid probability" condition when "x not in [0, 1]".
INVALID_PROBABILITY - Static variable in exception org.apache.commons.statistics.inference.InferenceException
Error message for "invalid probability" condition when "x not in [0, 1]".
INVALID_RANGE_LOW_GT_HIGH - Static variable in exception org.apache.commons.statistics.distribution.DistributionException
Error message for "invalid range" condition when "lower > upper".
INVALID_RANGE_LOW_GTE_HIGH - Static variable in exception org.apache.commons.statistics.distribution.DistributionException
Error message for "invalid range" condition when "lower >= upper".
INVALID_SIGNIFICANCE - Static variable in exception org.apache.commons.statistics.inference.InferenceException
Error message for "invalid significance" condition when "x not in (0, 0.5]".
INVALID_SIZE - Static variable in class org.apache.commons.statistics.descriptive.Quantile
Message when the size is not valid.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.AbstractContinuousDistribution
Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.AbstractDiscreteDistribution
Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.CauchyDistribution
Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.ChiSquaredDistribution
Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in interface org.apache.commons.statistics.distribution.ContinuousDistribution
Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in interface org.apache.commons.statistics.distribution.DiscreteDistribution
Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.ExponentialDistribution
Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.HalfNormalDistribution
 
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.GeometricDistribution
Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.GumbelDistribution
Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
 
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.LaplaceDistribution
Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.LevyDistribution
Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.LogisticDistribution
Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.LogNormalDistribution
Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.LogUniformDistribution
Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.NormalDistribution
Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.ParetoDistribution
Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.TDistribution.NormalTDistribution
 
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.DelegatedTrapezoidalDistribution
 
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.RegularTrapezoidalDistribution
 
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.TriangularDistribution
Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.UniformContinuousDistribution
Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.UniformDiscreteDistribution
Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.WeibullDistribution
Computes the quantile function of this distribution.
inverseLower(double, double, boolean) - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
Compute the inverse cumulative or survival probability using the lower sum.
inverseProbability(double, double, boolean) - Method in class org.apache.commons.statistics.distribution.AbstractContinuousDistribution
Implementation for the inverse cumulative or survival probability.
inverseProbability(double, double, boolean) - Method in class org.apache.commons.statistics.distribution.AbstractDiscreteDistribution
Implementation for the inverse cumulative or survival probability.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.AbstractContinuousDistribution
Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.AbstractDiscreteDistribution
Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.CauchyDistribution
Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.ChiSquaredDistribution
Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in interface org.apache.commons.statistics.distribution.ContinuousDistribution
Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in interface org.apache.commons.statistics.distribution.DiscreteDistribution
Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.ExponentialDistribution
Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.HalfNormalDistribution
Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.GeometricDistribution
Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.GumbelDistribution
Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
 
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.LaplaceDistribution
Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.LevyDistribution
Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.LogisticDistribution
Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.LogNormalDistribution
Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.LogUniformDistribution
 
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.NormalDistribution
Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.ParetoDistribution
Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.TDistribution
Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.DelegatedTrapezoidalDistribution
 
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.RegularTrapezoidalDistribution
 
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.TriangularDistribution
Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.UniformContinuousDistribution
Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.UniformDiscreteDistribution
Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.WeibullDistribution
Computes the inverse survival probability function of this distribution.
inverseUpper(double, double, boolean) - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
Compute the inverse cumulative or survival probability using the upper sum.
isBiased() - Method in class org.apache.commons.statistics.descriptive.StatisticsConfiguration
Checks if the calculation of the statistic is biased.
isEmpty() - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest.XYList
Checks if the list size is zero.
isFiniteStrictlyPositive(double) - Static method in class org.apache.commons.statistics.distribution.ArgumentUtils
Checks if the value x is finite and strictly positive.
isFull() - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest.XYList
Checks if the list is the maximum capacity.
isSupportConnected() - Method in class org.apache.commons.statistics.distribution.AbstractContinuousDistribution
Indicates whether the support is connected, i.e.
isSupported(Statistic) - Method in class org.apache.commons.statistics.descriptive.DoubleStatistics
Check if the specified statistic is supported.
isSupported(Statistic) - Method in class org.apache.commons.statistics.descriptive.IntStatistics
Check if the specified statistic is supported.
isSupported(Statistic) - Method in class org.apache.commons.statistics.descriptive.LongStatistics
Check if the specified statistic is supported.
iterations - Variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
Number of iterations .

K

KolmogorovSmirnovDistribution - Class in org.apache.commons.statistics.inference
Computes the complementary probability for the one-sample Kolmogorov-Smirnov distribution.
KolmogorovSmirnovDistribution() - Constructor for class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution
No instances.
KolmogorovSmirnovDistribution.One - Class in org.apache.commons.statistics.inference
Computes the complementary probability P[D_n^+ >= x] for the one-sided one-sample Kolmogorov-Smirnov distribution.
KolmogorovSmirnovDistribution.One.ScaledPower - Interface in org.apache.commons.statistics.inference
Defines a scaled power function.
KolmogorovSmirnovDistribution.Two - Class in org.apache.commons.statistics.inference
Computes the complementary probability P[D_n >= x], or survival function (SF), for the two-sided one-sample Kolmogorov-Smirnov distribution.
KolmogorovSmirnovTest - Class in org.apache.commons.statistics.inference
Implements the Kolmogorov-Smirnov (K-S) test for equality of continuous distributions.
KolmogorovSmirnovTest(AlternativeHypothesis, PValueMethod, boolean, UniformRandomProvider, int) - Constructor for class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
 
KolmogorovSmirnovTest.OneResult - Class in org.apache.commons.statistics.inference
Result for the one-sample Kolmogorov-Smirnov test.
KolmogorovSmirnovTest.TwoResult - Class in org.apache.commons.statistics.inference
Result for the two-sample Kolmogorov-Smirnov test.
ksSum(double) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution
Computes P(sqrt(n) D_n > x), the limiting form for the distribution of Kolmogorov's D_n as described in Simard and L’Ecuyer (2011) (Eq.
Kurtosis - Class in org.apache.commons.statistics.descriptive
Computes the kurtosis of the available values.
Kurtosis() - Constructor for class org.apache.commons.statistics.descriptive.Kurtosis
Create an instance.
Kurtosis(SumOfFourthDeviations) - Constructor for class org.apache.commons.statistics.descriptive.Kurtosis
Creates an instance with the sum of fourth deviations from the mean.
KURTOSIS - org.apache.commons.statistics.descriptive.Statistic
Kurtosis.

L

LaplaceDistribution - Class in org.apache.commons.statistics.distribution
Implementation of the Laplace distribution.
LaplaceDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.LaplaceDistribution
 
LARGE_SAMPLE - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
When the largest sample size exceeds this value, 2-sample test AUTO p-value uses an asymptotic distribution to compute the p-value.
LENGTH_FOUR - Static variable in class org.apache.commons.statistics.descriptive.Kurtosis
4, the length limit where the kurtosis is undefined.
LENGTH_THREE - Static variable in class org.apache.commons.statistics.descriptive.Skewness
3, the length limit where the unbiased skewness is undefined.
LENGTH_TWO - Static variable in class org.apache.commons.statistics.descriptive.Kurtosis
2, the length limit where the biased skewness is undefined.
LENGTH_TWO - Static variable in class org.apache.commons.statistics.descriptive.Skewness
2, the length limit where the biased skewness is undefined.
LENGTH_TWO - Static variable in class org.apache.commons.statistics.descriptive.SumOfCubedDeviations
2, the length limit where the sum-of-cubed deviations is zero.
LESS_THAN - org.apache.commons.statistics.inference.AlternativeHypothesis
Represents a left-sided test.
LevyDistribution - Class in org.apache.commons.statistics.distribution
Implementation of the Lévy distribution.
LevyDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.LevyDistribution
 
LN_LN_2 - Static variable in class org.apache.commons.statistics.distribution.GumbelDistribution
ln(ln(2)).
LN_TWO - Static variable in class org.apache.commons.statistics.distribution.Constants
ln(2).
lo - Variable in class org.apache.commons.statistics.descriptive.Int128
low 64-bits.
lo - Variable in class org.apache.commons.statistics.inference.BracketFinder
Lower bound of the bracket.
lo32() - Method in class org.apache.commons.statistics.descriptive.UInt128
Return the low 32-bits as an int value.
lo32() - Method in class org.apache.commons.statistics.descriptive.UInt96
Return the lower 32-bits as an int value.
lo64() - Method in class org.apache.commons.statistics.descriptive.Int128
Return the lower 64-bits as a long value.
lo64() - Method in class org.apache.commons.statistics.descriptive.UInt128
Return the lower 64-bits as a long value.
lo64() - Method in class org.apache.commons.statistics.descriptive.UInt192
Return the lower 64-bits as a long value.
location - Variable in class org.apache.commons.statistics.distribution.CauchyDistribution
The location of this distribution.
LOCK - Static variable in class org.apache.commons.statistics.inference.MannWhitneyUTest
An object to use for synchonization when accessing the cache of F.
LOG_MIN_NORMAL - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
Approximate threshold for ln(MIN_NORMAL).
LOG_PG_MIN - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
Threshold for Pelz-Good where the 1 - CDF == 1.
log1mProbabilityOfSuccess - Variable in class org.apache.commons.statistics.distribution.GeometricDistribution
log(1 - p) where p is the probability of success.
log1mProbabilityOfSuccess - Variable in class org.apache.commons.statistics.distribution.PascalDistribution
The value of log(1-p), 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 - org.apache.commons.statistics.descriptive.Statistic
Maximum.
MAX_ARRAY_SIZE - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
Maximum length of an array.
MAX_CANDIDATES - Static variable in class org.apache.commons.statistics.inference.UnconditionedExactTest
Maximum number of candidate to optimize.
MAX_FACTORIAL - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
Maximum finite factorial.
MAX_FACTORIAL - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
Maximum finite factorial.
MAX_LCM_TWO_SAMPLE_EXACT_P - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
The maximum least common multiple (lcm) to attempt the exact p-value computation.
MAX_MEAN - Static variable in class org.apache.commons.statistics.distribution.PoissonDistribution
Upper bound on the mean to use the PoissonSampler.
MAX_TABLES - Static variable in class org.apache.commons.statistics.inference.UnconditionedExactTest
The maximum number of tables.
MAX_X - Static variable in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
The max allowed value for x where (x*x) will not overflow.
maxEvaluations - Variable in class org.apache.commons.statistics.inference.BracketFinder
Number of allowed function evaluations.
MAXIMAL - org.apache.commons.statistics.ranking.NaNStrategy
NaNs are considered maximal in the ordering, equivalent to (that is, tied with) positive infinity.
maximum - Variable in class org.apache.commons.statistics.descriptive.IntMax
Current maximum.
maximum - Variable in class org.apache.commons.statistics.descriptive.LongMax
Current maximum.
maximum - Variable in class org.apache.commons.statistics.descriptive.Max
Current maximum.
MAXIMUM - org.apache.commons.statistics.ranking.TiesStrategy
Tied values are assigned the maximum applicable rank, or the rank of the last occurrence.
mean - Variable in class org.apache.commons.statistics.distribution.BetaDistribution
Cached value for inverse probability function.
mean - Variable in class org.apache.commons.statistics.distribution.ExponentialDistribution
The mean of this distribution.
mean - Variable in class org.apache.commons.statistics.distribution.FDistribution
Cached value for inverse probability function.
mean - Variable in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.RegularFoldedNormalDistribution
Cached value for inverse probability function.
mean - Variable in class org.apache.commons.statistics.distribution.GammaDistribution
Cached value for inverse probability function.
mean - Variable in class org.apache.commons.statistics.distribution.NakagamiDistribution
Cached value for inverse probability function.
mean - Variable in class org.apache.commons.statistics.distribution.NormalDistribution
Mean of this distribution.
mean - Variable in class org.apache.commons.statistics.distribution.PoissonDistribution
Mean of the distribution.
mean - Variable in class org.apache.commons.statistics.distribution.TDistribution.StudentsTDistribution
Cached value for inverse probability function.
mean(double, double) - Static method in class org.apache.commons.statistics.descriptive.Interpolation
Compute the arithmetic mean of the two values taking care to avoid overflow.
mean(int, int) - Static method in class org.apache.commons.statistics.descriptive.Interpolation
Compute the arithmetic mean of the two values.
mean(Collection<double[]>) - Static method in class org.apache.commons.statistics.inference.StatisticUtils
Returns the arithmetic mean of the entries in the input arrays, or NaN if the combined length of the arrays is zero.
Mean - Class in org.apache.commons.statistics.descriptive
Computes the arithmetic mean of the available values.
Mean() - Constructor for class org.apache.commons.statistics.descriptive.Mean
Create an instance.
Mean(FirstMoment) - Constructor for class org.apache.commons.statistics.descriptive.Mean
Creates an instance with a moment.
MEAN - org.apache.commons.statistics.descriptive.Statistic
Mean, or average.
meanDifference(double[], double[]) - Static method in class org.apache.commons.statistics.inference.StatisticUtils
Returns the mean of the (signed) differences between corresponding elements of the input arrays.
median - Variable in class org.apache.commons.statistics.distribution.AbstractContinuousDistribution
Cached value of the median.
median - Variable in class org.apache.commons.statistics.distribution.AbstractDiscreteDistribution
Cached value of the median.
Median - Class in org.apache.commons.statistics.descriptive
Returns the median of the available values.
Median(boolean, NaNPolicy) - Constructor for class org.apache.commons.statistics.descriptive.Median
 
method - Variable in class org.apache.commons.statistics.inference.UnconditionedExactTest
Method to identify more extreme tables.
Method() - Constructor for enum org.apache.commons.statistics.inference.UnconditionedExactTest.Method
 
mid - Variable in class org.apache.commons.statistics.inference.BracketFinder
Point inside the bracket.
mid32() - Method in class org.apache.commons.statistics.descriptive.UInt128
Return the middle 32-bits as an int value.
mid64() - Method in class org.apache.commons.statistics.descriptive.UInt192
Return the middle 64-bits as a long value.
midCDF - Variable in class org.apache.commons.statistics.inference.Hypergeom
Cached CDF of the midpoint.
midpoint - Variable in class org.apache.commons.statistics.distribution.HypergeometricDistribution
Cached midpoint of the CDF/SF.
min - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
The Min constructor.
min - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics
The Min implementation.
min - Variable in class org.apache.commons.statistics.descriptive.IntStatistics.Builder
The IntMin constructor.
min - Variable in class org.apache.commons.statistics.descriptive.IntStatistics
The IntMin implementation.
min - Variable in class org.apache.commons.statistics.descriptive.LongStatistics.Builder
The LongMin constructor.
min - Variable in class org.apache.commons.statistics.descriptive.LongStatistics
The LongMin implementation.
min - Variable in class org.apache.commons.statistics.inference.UnconditionedExactTest.Candidates
Current minimum.
Min - Class in org.apache.commons.statistics.descriptive
Returns the minimum of the available values.
Min() - Constructor for class org.apache.commons.statistics.descriptive.Min
Create an instance.
MIN - org.apache.commons.statistics.descriptive.Statistic
Minimum.
MIN_DENOMINATOR_DF_FOR_MEAN - Static variable in class org.apache.commons.statistics.distribution.FDistribution
The minimum degrees of freedom for the denominator when computing the mean.
MIN_DENOMINATOR_DF_FOR_VARIANCE - Static variable in class org.apache.commons.statistics.distribution.FDistribution
The minimum degrees of freedom for the denominator when computing the variance.
MIN_P - Static variable in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
The min allowed probability range of the parent normal distribution.
MIN_RELATIVE_TOLERANCE - Static variable in class org.apache.commons.statistics.inference.BrentOptimizer
Minimum relative tolerance.
MIN_SHAPE_FOR_VARIANCE - Static variable in class org.apache.commons.statistics.distribution.ParetoDistribution
The minimum value for the shape parameter when computing when computing the variance.
MINIMA_EPS - Static variable in class org.apache.commons.statistics.inference.UnconditionedExactTest
Relative distance of candidate minima from the lowest candidate.
MINIMAL - org.apache.commons.statistics.ranking.NaNStrategy
NaNs are considered minimal in the ordering, equivalent to (that is, tied with) negative infinity.
minimum - Variable in class org.apache.commons.statistics.descriptive.IntMin
Current minimum.
minimum - Variable in class org.apache.commons.statistics.descriptive.LongMin
Current minimum.
minimum - Variable in class org.apache.commons.statistics.descriptive.Min
Current minimum.
MINIMUM - org.apache.commons.statistics.ranking.TiesStrategy
Tied values are assigned the minimum applicable rank, or the rank of the first occurrence.
minusLogGammaShapeMinusLogScale - Variable in class org.apache.commons.statistics.distribution.GammaDistribution
Precomputed term for the log density: -log(gamma(shape)) - log(scale).
moment - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
The moment constructor.
moment - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics
The moment implementation.
moment - Variable in class org.apache.commons.statistics.descriptive.IntStatistics.Builder
The moment constructor.
moment - Variable in class org.apache.commons.statistics.descriptive.IntStatistics
The moment implementation.
moment - Variable in class org.apache.commons.statistics.descriptive.LongStatistics.Builder
The moment constructor.
moment - Variable in class org.apache.commons.statistics.descriptive.LongStatistics
The moment implementation.
moment1(double, double) - Static method in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
Compute the first moment (mean) of the truncated standard normal distribution.
moment2(double, double) - Static method in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
Compute the second moment of the truncated standard normal distribution.
momentOrder - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
The order of the moment.
momentOrder - Variable in class org.apache.commons.statistics.descriptive.IntStatistics.Builder
The order of the moment.
momentOrder - Variable in class org.apache.commons.statistics.descriptive.LongStatistics.Builder
The order of the moment.
msbg - Variable in class org.apache.commons.statistics.inference.OneWayAnova.Result
Mean square between groups.
mswg - Variable in class org.apache.commons.statistics.inference.OneWayAnova.Result
Mean square within groups.
MTW_SCALE_THRESHOLD - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
The scaling threshold in the MTW algorithm.
MTW_UP_SCALE - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
The up-scaling factor in the MTW algorithm.
MTW_UP_SCALE_POWER - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
The power-of-2 of the up-scaling factor in the MTW algorithm, n if the up-scale factor is 2^n.
mu - Variable in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.RegularFoldedNormalDistribution
The location.
mu - Variable in class org.apache.commons.statistics.distribution.GumbelDistribution
Location parameter.
mu - Variable in class org.apache.commons.statistics.distribution.LaplaceDistribution
The location parameter.
mu - Variable in class org.apache.commons.statistics.distribution.LevyDistribution
Location parameter.
mu - Variable in class org.apache.commons.statistics.distribution.LogisticDistribution
Location parameter.
mu - Variable in class org.apache.commons.statistics.distribution.LogNormalDistribution
The mu parameter of this distribution.
mu - Variable in class org.apache.commons.statistics.distribution.NakagamiDistribution
The shape parameter.
mu - Variable in class org.apache.commons.statistics.inference.MannWhitneyUTest
Expected location shift.
mu - Variable in class org.apache.commons.statistics.inference.TTest
The true value of the mean (or difference in means for a two sample test).
mu - Variable in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
Expected location shift.
multiply(double[], int, double[], int, double[], double[]) - Static method in class org.apache.commons.statistics.inference.SquareMatrixSupport.ArrayRealSquareMatrix
Returns the result of postmultiplying a 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 FAILED and TiesStrategy.AVERAGE.
NaturalRanking(IntUnaryOperator) - Constructor for class org.apache.commons.statistics.ranking.NaturalRanking
Creates an instance with FAILED, TiesStrategy.RANDOM and the given the source of random index data.
NaturalRanking(NaNStrategy) - Constructor for class org.apache.commons.statistics.ranking.NaturalRanking
Creates an instance with the specified @nanStrategy and TiesStrategy.AVERAGE.
NaturalRanking(NaNStrategy, IntUnaryOperator) - Constructor for class org.apache.commons.statistics.ranking.NaturalRanking
Creates an instance with the specified @nanStrategy, TiesStrategy.RANDOM and the given the source of random index data.
NaturalRanking(NaNStrategy, TiesStrategy) - Constructor for class org.apache.commons.statistics.ranking.NaturalRanking
Creates an instance with the specified @nanStrategy and the specified @tiesStrategy.
NaturalRanking(NaNStrategy, TiesStrategy, IntUnaryOperator) - Constructor for class org.apache.commons.statistics.ranking.NaturalRanking
 
NaturalRanking(TiesStrategy) - Constructor for class org.apache.commons.statistics.ranking.NaturalRanking
Creates an instance with FAILED and the specified @tiesStrategy.
NaturalRanking.DataPosition - Class in org.apache.commons.statistics.ranking
Represents the position of a double value in a data array.
NaturalRanking.IntList - Class in org.apache.commons.statistics.ranking
An expandable list of int values.
nDev - Variable in class org.apache.commons.statistics.descriptive.FirstMoment
Half the deviation of most recently added value from the previous first moment, normalized by current sample size.
NEGATIVE - Static variable in exception org.apache.commons.statistics.distribution.DistributionException
Error message for "negative" condition when x < 0.
NEGATIVE - Static variable in exception org.apache.commons.statistics.inference.InferenceException
Error message for "negative" condition when "x < 0".
nHalfLogNmHalfLogM - Variable in class org.apache.commons.statistics.distribution.FDistribution
n/2 * log(n) + m/2 * log(m) with n = numerator DF and m = denominator DF.
nO - Variable in class org.apache.commons.statistics.inference.OneWayAnova.Result
nO value used to partition the variance.
NO_CONFIGURED_STATISTICS - Static variable in class org.apache.commons.statistics.descriptive.DoubleStatistics
Error message for non configured statistics.
NO_CONFIGURED_STATISTICS - Static variable in class org.apache.commons.statistics.descriptive.IntStatistics
Error message for non configured statistics.
NO_CONFIGURED_STATISTICS - Static variable in class org.apache.commons.statistics.descriptive.LongStatistics
Error message for non configured statistics.
NO_DATA - Static variable in exception org.apache.commons.statistics.inference.InferenceException
Error message for "no data" condition.
NO_MEDIAN - Static variable in class org.apache.commons.statistics.distribution.AbstractDiscreteDistribution
Marker value for no median.
NO_PROBABILITIES_SPECIFIED - Static variable in class org.apache.commons.statistics.descriptive.Quantile
Message when no probabilities are provided for the varargs method.
NO_VALUES - Static variable in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
An empty double array.
NO_VALUES - Static variable in class org.apache.commons.statistics.descriptive.IntStatistics.Builder
An empty double array.
NO_VALUES - Static variable in class org.apache.commons.statistics.descriptive.LongStatistics.Builder
An empty double array.
NON_STRICT - org.apache.commons.statistics.inference.Inequality
Represents a non-strict inequality (numbers may be equal).
nonCentralMoment(int, double, double) - Static method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.RegularTrapezoidalDistribution
Compute the k-th non-central moment of the standardized trapezoidal distribution.
nonFiniteValue - Variable in class org.apache.commons.statistics.descriptive.FirstMoment
Running sum of values seen so far.
NormalDistribution - Class in org.apache.commons.statistics.distribution
Implementation of the normal (Gaussian) distribution.
NormalDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.NormalDistribution
 
NormalTDistribution(double) - Constructor for class org.apache.commons.statistics.distribution.TDistribution.NormalTDistribution
 
NOT_RECTANGULAR - Static variable in exception org.apache.commons.statistics.inference.InferenceException
Error message for "non-rectangular matrix" when "some row lengths x != others y".
NOT_STRICTLY_POSITIVE - Static variable in exception org.apache.commons.statistics.distribution.DistributionException
Error message for "not strictly positive" condition when x <= 0.
NOT_STRICTLY_POSITIVE - Static variable in exception org.apache.commons.statistics.inference.InferenceException
Error message for "not strictly positive" condition when "x <= 0".
NOT_STRICTLY_POSITIVE_FINITE - Static variable in exception org.apache.commons.statistics.distribution.DistributionException
Error message for "not strictly positive finite" condition when x <= 0 || x == inf.
nthHarmonic - Variable in class org.apache.commons.statistics.distribution.ZipfDistribution
Cached value of the nth generalized harmonic.
NULL_NAN_STRATEGY - Static variable in class org.apache.commons.statistics.ranking.NaturalRanking
Message for a null user-supplied NaNStrategy.
NULL_RANDOM_SOURCE - Static variable in class org.apache.commons.statistics.ranking.NaturalRanking
Message for a null user-supplied source of randomness.
NULL_TIES_STRATEGY - Static variable in class org.apache.commons.statistics.ranking.NaturalRanking
Message for a null user-supplied TiesStrategy.
numberOfElements - Variable in class org.apache.commons.statistics.distribution.ZipfDistribution
Number of elements.
numberOfSuccesses - Variable in class org.apache.commons.statistics.distribution.HypergeometricDistribution
The number of successes in the population.
numberOfSuccesses - Variable in class org.apache.commons.statistics.distribution.PascalDistribution
The number of successes.
numberOfTrials - Variable in class org.apache.commons.statistics.distribution.BinomialDistribution
The number of trials.
numeratorDegreesOfFreedom - Variable in class org.apache.commons.statistics.distribution.FDistribution
The numerator degrees of freedom.
NX32_1_4 - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
1.4, nx^(3/2) threshold for large n Durbin matrix sf computation.
NXX_0_754693 - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
0.754693, nxx threshold for small n Durbin matrix sf computation.
NXX_2_2 - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
2.2, nxx threshold for large n Miller approximation sf computation.
NXX_4 - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
4, nxx threshold for small n Pomeranz sf computation.

O

of(double) - Static method in class org.apache.commons.statistics.distribution.ChiSquaredDistribution
Creates a chi-squared distribution.
of(double) - Static method in class org.apache.commons.statistics.distribution.ExponentialDistribution
Creates an exponential distribution.
of(double) - Static method in class org.apache.commons.statistics.distribution.GeometricDistribution
Creates a geometric distribution.
of(double) - Static method in class org.apache.commons.statistics.distribution.PoissonDistribution
Creates a Poisson distribution.
of(double) - Static method in class org.apache.commons.statistics.distribution.TDistribution
Creates a Student's t-distribution.
of(double...) - Static method in class org.apache.commons.statistics.descriptive.FirstMoment
Returns an instance populated using the input values.
of(double...) - Static method in class org.apache.commons.statistics.descriptive.GeometricMean
Returns an instance populated using the input values.
of(double...) - Static method in class org.apache.commons.statistics.descriptive.Kurtosis
Returns an instance populated using the input values.
of(double...) - Static method in class org.apache.commons.statistics.descriptive.Max
Returns an instance populated using the input values.
of(double...) - Static method in class org.apache.commons.statistics.descriptive.Mean
Returns an instance populated using the input values.
of(double...) - Static method in class org.apache.commons.statistics.descriptive.Min
Returns an instance populated using the input values.
of(double...) - Static method in class org.apache.commons.statistics.descriptive.Product
Returns an instance populated using the input values.
of(double...) - Static method in class org.apache.commons.statistics.descriptive.Skewness
Returns an instance populated using the input values.
of(double...) - Static method in class org.apache.commons.statistics.descriptive.StandardDeviation
Returns an instance populated using the input values.
of(double...) - Static method in class org.apache.commons.statistics.descriptive.Sum
Returns an instance populated using the input values.
of(double...) - Static method in class org.apache.commons.statistics.descriptive.SumOfCubedDeviations
Returns an instance populated using the input values.
of(double...) - Static method in class org.apache.commons.statistics.descriptive.SumOfFourthDeviations
Returns an instance populated using the input values.
of(double...) - Static method in class org.apache.commons.statistics.descriptive.SumOfLogs
Returns an instance populated using the input values.
of(double...) - Static method in class org.apache.commons.statistics.descriptive.SumOfSquaredDeviations
Returns an instance populated using the input values.
of(double...) - Static method in class org.apache.commons.statistics.descriptive.SumOfSquares
Returns an instance populated using the input values.
of(double...) - Static method in class org.apache.commons.statistics.descriptive.Variance
Returns an instance populated using the input values.
of(double, double) - Static method in class org.apache.commons.statistics.distribution.BetaDistribution
Creates a beta distribution.
of(double, double) - Static method in class org.apache.commons.statistics.distribution.CauchyDistribution
Creates a Cauchy distribution.
of(double, double) - Static method in class org.apache.commons.statistics.distribution.FDistribution
Creates an F-distribution.
of(double, double) - Static method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution
Creates a folded normal distribution.
of(double, double) - Static method in class org.apache.commons.statistics.distribution.GammaDistribution
Creates a gamma distribution.
of(double, double) - Static method in class org.apache.commons.statistics.distribution.GumbelDistribution
Creates a Gumbel distribution.
of(double, double) - Static method in class org.apache.commons.statistics.distribution.LaplaceDistribution
Creates a Laplace distribution.
of(double, double) - Static method in class org.apache.commons.statistics.distribution.LevyDistribution
Creates a Levy distribution.
of(double, double) - Static method in class org.apache.commons.statistics.distribution.LogisticDistribution
Creates a logistic distribution.
of(double, double) - Static method in class org.apache.commons.statistics.distribution.LogNormalDistribution
Creates a log-normal distribution.
of(double, double) - Static method in class org.apache.commons.statistics.distribution.LogUniformDistribution
Creates a log-uniform distribution.
of(double, double) - Static method in class org.apache.commons.statistics.distribution.NakagamiDistribution
Creates a Nakagami distribution.
of(double, double) - Static method in class org.apache.commons.statistics.distribution.NormalDistribution
Creates a normal distribution.
of(double, double) - Static method in class org.apache.commons.statistics.distribution.ParetoDistribution
Creates a Pareto distribution.
of(double, double) - Static method in class org.apache.commons.statistics.distribution.UniformContinuousDistribution
Creates a uniform continuous distribution.
of(double, double) - Static method in class org.apache.commons.statistics.distribution.WeibullDistribution
Creates a Weibull distribution.
of(double, double) - Static method in class org.apache.commons.statistics.inference.BrentOptimizer.PointValuePair
Create a point/objective function value pair.
of(double, double, double) - Static method in class org.apache.commons.statistics.distribution.TriangularDistribution
Creates a triangular distribution.
of(double, double, double, double) - Static method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution
Creates a trapezoidal distribution.
of(double, double, double, double) - Static method in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
Creates a truncated normal distribution.
of(int...) - Static method in class org.apache.commons.statistics.descriptive.GeometricMean
Returns an instance populated using the input values.
of(int...) - Static method in class org.apache.commons.statistics.descriptive.IntMax
Returns an instance populated using the input values.
of(int...) - Static method in class org.apache.commons.statistics.descriptive.IntMean
Returns an instance populated using the input values.
of(int...) - Static method in class org.apache.commons.statistics.descriptive.IntMin
Returns an instance populated using the input values.
of(int...) - Static method in class org.apache.commons.statistics.descriptive.IntStandardDeviation
Returns an instance populated using the input values.
of(int...) - Static method in class org.apache.commons.statistics.descriptive.IntSum
Returns an instance populated using the input values.
of(int...) - Static method in class org.apache.commons.statistics.descriptive.IntSumOfSquares
Returns an instance populated using the input values.
of(int...) - Static method in class org.apache.commons.statistics.descriptive.IntVariance
Returns an instance populated using the input values.
of(int...) - Static method in class org.apache.commons.statistics.descriptive.Kurtosis
Returns an instance populated using the input values.
of(int...) - Static method in class org.apache.commons.statistics.descriptive.Product
Returns an instance populated using the input values.
of(int...) - Static method in class org.apache.commons.statistics.descriptive.Skewness
Returns an instance populated using the input values.
of(int...) - Static method in class org.apache.commons.statistics.descriptive.SumOfCubedDeviations
Returns an instance populated using the input values.
of(int...) - Static method in class org.apache.commons.statistics.descriptive.SumOfFourthDeviations
Returns an instance populated using the input values.
of(int...) - Static method in class org.apache.commons.statistics.descriptive.SumOfLogs
Returns an instance populated using the input values.
of(int, double) - Static method in class org.apache.commons.statistics.distribution.BinomialDistribution
Creates a binomial distribution.
of(int, double) - Static method in class org.apache.commons.statistics.distribution.PascalDistribution
Create a Pascal distribution.
of(int, double) - Static method in class org.apache.commons.statistics.distribution.ZipfDistribution
Creates a Zipf distribution.
of(int, int) - Static method in class org.apache.commons.statistics.distribution.UniformDiscreteDistribution
Creates a new uniform discrete distribution.
of(int, int, int) - Static method in class org.apache.commons.statistics.distribution.HypergeometricDistribution
Creates a hypergeometric distribution.
of(long) - Static method in class org.apache.commons.statistics.descriptive.Int128
Create an instance of the long value.
of(long) - Static method in class org.apache.commons.statistics.descriptive.UInt96
Create an instance of the long value.
of(long...) - Static method in class org.apache.commons.statistics.descriptive.GeometricMean
Returns an instance populated using the input values.
of(long...) - Static method in class org.apache.commons.statistics.descriptive.Kurtosis
Returns an instance populated using the input values.
of(long...) - Static method in class org.apache.commons.statistics.descriptive.LongMax
Returns an instance populated using the input values.
of(long...) - Static method in class org.apache.commons.statistics.descriptive.LongMean
Returns an instance populated using the input values.
of(long...) - Static method in class org.apache.commons.statistics.descriptive.LongMin
Returns an instance populated using the input values.
of(long...) - Static method in class org.apache.commons.statistics.descriptive.LongStandardDeviation
Returns an instance populated using the input values.
of(long...) - Static method in class org.apache.commons.statistics.descriptive.LongSum
Returns an instance populated using the input values.
of(long...) - Static method in class org.apache.commons.statistics.descriptive.LongSumOfSquares
Returns an instance populated using the input values.
of(long...) - Static method in class org.apache.commons.statistics.descriptive.LongVariance
Returns an instance populated using the input values.
of(long...) - Static method in class org.apache.commons.statistics.descriptive.Product
Returns an instance populated using the input values.
of(long...) - Static method in class org.apache.commons.statistics.descriptive.Skewness
Returns an instance populated using the input values.
of(long...) - Static method in class org.apache.commons.statistics.descriptive.SumOfCubedDeviations
Returns an instance populated using the input values.
of(long...) - Static method in class org.apache.commons.statistics.descriptive.SumOfFourthDeviations
Returns an instance populated using the input values.
of(long...) - Static method in class org.apache.commons.statistics.descriptive.SumOfLogs
Returns an instance populated using the input values.
of(Set<Statistic>, double...) - Static method in class org.apache.commons.statistics.descriptive.DoubleStatistics
Returns a new instance configured to compute the specified statistics populated using the 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 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 - org.apache.commons.statistics.descriptive.Statistic
Product.
productValue - Variable in class org.apache.commons.statistics.descriptive.Product
Product of all values.
pValueMethod - Variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
Method to compute the p-value.
pValueMethod - Variable in class org.apache.commons.statistics.inference.MannWhitneyUTest
Method to compute the p-value.
pValueMethod - Variable in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
Method to compute the p-value.
PValueMethod - Enum in org.apache.commons.statistics.inference
Represents a method for computing a p-value for a test statistic.
PValueMethod() - Constructor for enum org.apache.commons.statistics.inference.PValueMethod
 

Q

Quantile - Class in org.apache.commons.statistics.descriptive
Provides quantile computation.
Quantile(boolean, NaNPolicy, Quantile.EstimationMethod) - Constructor for class org.apache.commons.statistics.descriptive.Quantile
 
Quantile.EstimationMethod - Enum in org.apache.commons.statistics.descriptive
Estimation methods for a quantile.

R

RANDOM - org.apache.commons.statistics.ranking.TiesStrategy
Tied values are assigned a unique random integral rank from among the applicable values.
randomIntFunction - Variable in class org.apache.commons.statistics.ranking.NaturalRanking
Source of randomness when ties strategy is RANDOM.
RANKING - Static variable in class org.apache.commons.statistics.inference.MannWhitneyUTest
Ranking instance.
RANKING - Static variable in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
Ranking instance.
RankingAlgorithm - Interface in org.apache.commons.statistics.ranking
Interface representing a rank transformation.
RegularFoldedNormalDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.FoldedNormalDistribution.RegularFoldedNormalDistribution
 
RegularTrapezoidalDistribution(double, double, double, double) - Constructor for class org.apache.commons.statistics.distribution.TrapezoidalDistribution.RegularTrapezoidalDistribution
 
reject(double) - Method in interface org.apache.commons.statistics.inference.SignificanceResult
Returns true iff the null hypothesis can be rejected with 100 * (1 - alpha) percent confidence.
REJECTION_THRESHOLD - Static variable in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
The threshold to switch to a rejection sampler.
relativeThreshold - Variable in class org.apache.commons.statistics.inference.BrentOptimizer
Relative threshold.
REMOVED - org.apache.commons.statistics.ranking.NaNStrategy
NaNs are removed before rank transform is applied.
replaceWorst(double, double) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest.Candidates
Replace the worst candidate.
RESCALE - Static variable in class org.apache.commons.statistics.descriptive.FirstMoment
The rescale constant.
resolveTie(double[], NaturalRanking.IntList, int) - Method in class org.apache.commons.statistics.ranking.NaturalRanking
Resolve a sequence of ties, using the configured TiesStrategy.
Result(double) - Constructor for class org.apache.commons.statistics.inference.UnconditionedExactTest.Result
Create an instance where all tables are more extreme, i.e.
Result(double, boolean, boolean, double) - Constructor for class org.apache.commons.statistics.inference.WilcoxonSignedRankTest.Result
Create an instance.
Result(double, boolean, double) - Constructor for class org.apache.commons.statistics.inference.MannWhitneyUTest.Result
Create an instance.
Result(double, double, double) - Constructor for class org.apache.commons.statistics.inference.TTest.Result
Create an instance.
Result(double, double, double) - Constructor for class org.apache.commons.statistics.inference.UnconditionedExactTest.Result
 
Result(int, long, double, double, double, double, double) - Constructor for class org.apache.commons.statistics.inference.OneWayAnova.Result
 
rng - Variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
Source of randomness.
ROOT_2_PI - Static variable in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
Normalisation constant 2 / sqrt(2 pi) = sqrt(2 / pi).
ROOT_HALF_PI - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
sqrt(pi/2).
ROOT_PI_2 - Static variable in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
Normalisation constant sqrt(2 pi) / 2 = sqrt(pi / 2).
ROOT_PI_DIV_TWO - Static variable in class org.apache.commons.statistics.distribution.Constants
sqrt(pi / 2).
ROOT_TWO - Static variable in class org.apache.commons.statistics.distribution.Constants
sqrt(2).
ROOT_TWO_DIV_PI - Static variable in class org.apache.commons.statistics.distribution.Constants
sqrt(2 / pi).
ROOT_TWO_PI - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution
sqrt(2*pi).
ROOT_TWO_PI - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
sqrt(2*pi).
ROOT2 - Static variable in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
sqrt(2).
roundToInteger(double) - Static method in class org.apache.commons.statistics.descriptive.IntMath
Get the whole number that is the nearest to x, with ties rounding towards positive infinity.
ROW - Static variable in class org.apache.commons.statistics.inference.ChiSquareTest
Name for the row.

S

SaddlePointExpansionUtils - Class in org.apache.commons.statistics.distribution
Utility class used by various distributions to accurately compute their respective probability mass functions.
SaddlePointExpansionUtils() - Constructor for class org.apache.commons.statistics.distribution.SaddlePointExpansionUtils
Forbid construction.
sample() - Method in interface org.apache.commons.statistics.distribution.ContinuousDistribution.Sampler
Generates a random value sampled from this distribution.
sample() - Method in interface org.apache.commons.statistics.distribution.DiscreteDistribution.Sampler
Generates a random value sampled from this distribution.
SAMPLE_1_NAME - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
Name for sample 1.
SAMPLE_2_NAME - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
Name for sample 2.
samples() - Method in interface org.apache.commons.statistics.distribution.ContinuousDistribution.Sampler
Returns an effectively unlimited stream of double sample values.
samples() - Method in interface org.apache.commons.statistics.distribution.DiscreteDistribution.Sampler
Returns an effectively unlimited stream of int sample values.
samples(long) - Method in interface org.apache.commons.statistics.distribution.ContinuousDistribution.Sampler
Returns a stream producing the given streamSize number 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 - org.apache.commons.statistics.ranking.TiesStrategy
Ties are assigned ranks in order of occurrence in the original array.
serialVersionUID - Static variable in exception org.apache.commons.statistics.distribution.DistributionException
Serializable version identifier.
serialVersionUID - Static variable in exception org.apache.commons.statistics.inference.InferenceException
Serializable version identifier.
setBiased(boolean) - Method in class org.apache.commons.statistics.descriptive.IntStandardDeviation
Sets the value of the biased flag.
setBiased(boolean) - Method in class org.apache.commons.statistics.descriptive.IntVariance
Sets the value of the biased flag.
setBiased(boolean) - Method in class org.apache.commons.statistics.descriptive.Kurtosis
Sets the value of the biased flag.
setBiased(boolean) - Method in class org.apache.commons.statistics.descriptive.LongStandardDeviation
Sets the value of the biased flag.
setBiased(boolean) - Method in class org.apache.commons.statistics.descriptive.LongVariance
Sets the value of the biased flag.
setBiased(boolean) - Method in class org.apache.commons.statistics.descriptive.Skewness
Sets the value of the biased flag.
setBiased(boolean) - Method in class org.apache.commons.statistics.descriptive.StandardDeviation
Sets the value of the biased flag.
setBiased(boolean) - Method in class org.apache.commons.statistics.descriptive.Variance
Sets the value of the biased flag.
setConfiguration(StatisticsConfiguration) - Method in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
Sets the statistics configuration options for computation of statistics.
setConfiguration(StatisticsConfiguration) - Method in class org.apache.commons.statistics.descriptive.DoubleStatistics
Sets the statistics configuration.
setConfiguration(StatisticsConfiguration) - Method in class org.apache.commons.statistics.descriptive.IntStatistics.Builder
Sets the statistics configuration options for computation of statistics.
setConfiguration(StatisticsConfiguration) - Method in class org.apache.commons.statistics.descriptive.IntStatistics
Sets the statistics configuration.
setConfiguration(StatisticsConfiguration) - Method in class org.apache.commons.statistics.descriptive.LongStatistics.Builder
Sets the statistics configuration options for computation of statistics.
setConfiguration(StatisticsConfiguration) - Method in class org.apache.commons.statistics.descriptive.LongStatistics
Sets the statistics configuration.
sf(double, int) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.One
Calculates complementary probability P[D_n^+ >= x], or survival function (SF), for the one-sided one-sample Kolmogorov-Smirnov distribution.
sf(double, int) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
Calculates complementary probability P[D_n >= x] for the two-sided one-sample Kolmogorov-Smirnov distribution.
sf(double, int, KolmogorovSmirnovDistribution.One.ScaledPower) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.One
Calculates complementary probability P[D_n^+ >= x], or survival function (SF), for the one-sided one-sample Kolmogorov-Smirnov distribution.
sf(int) - Method in class org.apache.commons.statistics.inference.Hypergeom
Compute the survival function (SF) at the specified value.
sf(int, int, int) - Static method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
Compute the survival function of the Wilcoxon signed rank W+ statistic.
sf(int, int, int, int, double) - Static method in class org.apache.commons.statistics.inference.MannWhitneyUTest
Compute the survival function of the Mann-Whitney U1 statistic.
sf0 - Variable in class org.apache.commons.statistics.distribution.GeometricDistribution
Value of survival probability for x=0.
sf0 - Variable in class org.apache.commons.statistics.distribution.UniformDiscreteDistribution
Value of survival probability for x=0.
sfAsymptotic(double, int) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.One
Calculates complementary probability P[D_n^+ >= x], or survival function (SF), for the one-sided one-sample Kolmogorov-Smirnov distribution.
sfB - Variable in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.RegularTrapezoidalDistribution
Survival probability at b.
sfBeta - Variable in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
Stored value of parentNormal.survivalProbability(upper).
sfC - Variable in class org.apache.commons.statistics.distribution.TrapezoidalDistribution.RegularTrapezoidalDistribution
Survival probability at c.
sfExact(double, int) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.One
Calculates exact cases for the complementary probability P[D_n^+ >= x] the one-sided one-sample Kolmogorov-Smirnov distribution.
sfExact(double, int) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.Two
Calculates exact cases for the complementary probability P[D_n >= x] the two-sided one-sample Kolmogorov-Smirnov distribution.
sfMode - Variable in class org.apache.commons.statistics.distribution.TriangularDistribution
Survival probability at the mode.
shape - Variable in class org.apache.commons.statistics.distribution.GammaDistribution
The shape parameter.
shape - Variable in class org.apache.commons.statistics.distribution.ParetoDistribution
The shape parameter of this distribution.
shape - Variable in class org.apache.commons.statistics.distribution.WeibullDistribution
The shape parameter.
shapeOverScale - Variable in class org.apache.commons.statistics.distribution.WeibullDistribution
shape / scale.
shuffle(IntUnaryOperator) - Method in class org.apache.commons.statistics.ranking.NaturalRanking.IntList
Shuffle the list.
sigma - Variable in class org.apache.commons.statistics.distribution.FoldedNormalDistribution
The scale.
sigma - Variable in class org.apache.commons.statistics.distribution.LogNormalDistribution
The sigma parameter of this distribution.
sigmaSqrt2 - Variable in class org.apache.commons.statistics.distribution.FoldedNormalDistribution
The scale multiplied by sqrt(2).
sigmaSqrt2 - Variable in class org.apache.commons.statistics.distribution.LogNormalDistribution
Sigma multiplied by sqrt(2).
sigmaSqrt2pi - Variable in class org.apache.commons.statistics.distribution.FoldedNormalDistribution
The scale multiplied by sqrt(2 pi).
sigmaSqrt2Pi - Variable in class org.apache.commons.statistics.distribution.LogNormalDistribution
Sigma multiplied by sqrt(2 * pi).
sign - Variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest.OneResult
Sign of the statistic.
SignificanceResult - Interface in org.apache.commons.statistics.inference
Contains the result of a test for significance.
significantTies - Variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest.TwoResult
Flag to indicate there were significant ties.
size - Variable in class org.apache.commons.statistics.inference.UnconditionedExactTest.Candidates
Current size of the list.
size - Variable in class org.apache.commons.statistics.inference.UnconditionedExactTest.XYList
The size of the list.
size - Variable in class org.apache.commons.statistics.ranking.NaturalRanking.IntList
The size of the list.
size() - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest.XYList
Gets the number of elements in the list.
size() - Method in class org.apache.commons.statistics.ranking.NaturalRanking.IntList
Gets the number of elements in the list.
Skewness - Class in org.apache.commons.statistics.descriptive
Computes the skewness of the available values.
Skewness() - Constructor for class org.apache.commons.statistics.descriptive.Skewness
Create an instance.
Skewness(SumOfCubedDeviations) - Constructor for class org.apache.commons.statistics.descriptive.Skewness
Creates an instance with the sum of cubed deviations from the mean.
SKEWNESS - org.apache.commons.statistics.descriptive.Statistic
Skewness.
SMALL - Static variable in class org.apache.commons.statistics.distribution.ExtendedPrecision
Threshold for a small number that may underflow when squared.
SMALL_N - Static variable in class org.apache.commons.statistics.descriptive.IntMean
Limit for small sample size where the sum can exactly map to a double.
SMALL_SAMPLE - Static variable in class org.apache.commons.statistics.descriptive.IntSumOfSquares
Small array sample size.
SMALL_SAMPLE - Static variable in class org.apache.commons.statistics.descriptive.IntVariance
Small array sample size.
SMALL_SUM - Static variable in class org.apache.commons.statistics.descriptive.LongMean
Limit where the absolute sum can exactly map to a double.
solveInverseProbability(IntUnaryOperator, int, int) - Static method in class org.apache.commons.statistics.distribution.AbstractDiscreteDistribution
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 - 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 extends StatisticResult> - Interface in org.apache.commons.statistics.descriptive
A mutable result container that accumulates a StatisticResult.
statisticBoschloo(int, int, int, int) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest
Compute the statistic using Fisher's p-value (also known as Boschloo's test).
statisticBoschlooTwoSided(Hypergeom, int) - Static method in class org.apache.commons.statistics.inference.UnconditionedExactTest
Compute the two-sided statistic using Fisher's p-value (also known as Boschloo's test).
StatisticResult - Interface in org.apache.commons.statistics.descriptive
Represents the result of a statistic computed over a set of values.
Statistics - Class in org.apache.commons.statistics.descriptive
Utility methods for statistics.
Statistics() - Constructor for class org.apache.commons.statistics.descriptive.Statistics
No instances.
StatisticsConfiguration - Class in org.apache.commons.statistics.descriptive
Configuration for computation of statistics.
StatisticsConfiguration(boolean) - Constructor for class org.apache.commons.statistics.descriptive.StatisticsConfiguration
Create an instance.
StatisticUtils - Class in org.apache.commons.statistics.inference
Utility computation methods.
StatisticUtils() - Constructor for class org.apache.commons.statistics.inference.StatisticUtils
No instances.
statisticZ(int, int, int, int, boolean) - Static method in class org.apache.commons.statistics.inference.UnconditionedExactTest
Compute the statistic from a Z-test.
STIRLING_ERROR_THRESHOLD - Static variable in class org.apache.commons.statistics.distribution.SaddlePointExpansionUtils
The threshold value for switching the method to compute th Stirling error.
STRICT - org.apache.commons.statistics.inference.Inequality
Represents a strict inequality.
strictInequality - Variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
Use a strict inequality for the two-sample exact p-value.
StudentsTDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.TDistribution.StudentsTDistribution
 
subtract(double[], double) - Static method in class org.apache.commons.statistics.inference.StatisticUtils
Compute x - y.
subtract(UInt128) - Method in class org.apache.commons.statistics.descriptive.UInt128
Subtracts the value.
subtract(UInt128) - Method in class org.apache.commons.statistics.descriptive.UInt192
Subtracts the value.
sum - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
The Sum constructor.
sum - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics
The Sum implementation.
sum - Variable in class org.apache.commons.statistics.descriptive.IntMean
Sum of the values.
sum - Variable in class org.apache.commons.statistics.descriptive.IntStandardDeviation
Sum of the values.
sum - Variable in class org.apache.commons.statistics.descriptive.IntStatistics.Builder
The IntSum constructor.
sum - Variable in class org.apache.commons.statistics.descriptive.IntStatistics
The IntSum implementation.
sum - Variable in class org.apache.commons.statistics.descriptive.IntSum
Sum of the values.
sum - Variable in class org.apache.commons.statistics.descriptive.IntVariance
Sum of the values.
sum - Variable in class org.apache.commons.statistics.descriptive.LongMean
Sum of the values.
sum - Variable in class org.apache.commons.statistics.descriptive.LongStandardDeviation
Sum of the values.
sum - Variable in class org.apache.commons.statistics.descriptive.LongStatistics.Builder
The LongSum constructor.
sum - Variable in class org.apache.commons.statistics.descriptive.LongStatistics
The LongSum implementation.
sum - Variable in class org.apache.commons.statistics.descriptive.LongSum
Sum of the values.
sum - Variable in class org.apache.commons.statistics.descriptive.LongVariance
Sum of the values.
Sum - Class in org.apache.commons.statistics.descriptive
Returns the sum of the available values.
Sum() - Constructor for class org.apache.commons.statistics.descriptive.Sum
Create an instance.
Sum(Sum) - Constructor for class org.apache.commons.statistics.descriptive.Sum
Create an instance using the specified sum.
SUM - org.apache.commons.statistics.descriptive.Statistic
Sum.
SUM_OF_LOGS - org.apache.commons.statistics.descriptive.Statistic
Sum of the natural logarithm of values.
SUM_OF_SQUARES - org.apache.commons.statistics.descriptive.Statistic
Sum of the squared values.
SUM_PRECISION_BITS - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.One
Number of bits of precision in the sum of terms Aj.
sumCubedDev - Variable in class org.apache.commons.statistics.descriptive.SumOfCubedDeviations
Sum of cubed deviations of the values that have been added.
sumFourthDev - Variable in class org.apache.commons.statistics.descriptive.SumOfFourthDeviations
Sum of forth deviations of the values that have been added.
SumOfCubedDeviations - Class in org.apache.commons.statistics.descriptive
Computes the sum of cubed deviations from the sample mean.
SumOfCubedDeviations() - Constructor for class org.apache.commons.statistics.descriptive.SumOfCubedDeviations
Create an instance.
SumOfCubedDeviations(double, double, double, long) - Constructor for class org.apache.commons.statistics.descriptive.SumOfCubedDeviations
Create an instance with the given sum of cubed and squared deviations, and first moment.
SumOfCubedDeviations(double, SumOfSquaredDeviations) - Constructor for class org.apache.commons.statistics.descriptive.SumOfCubedDeviations
Create an instance with the given sum of cubed and squared deviations.
SumOfCubedDeviations(SumOfCubedDeviations) - Constructor for class org.apache.commons.statistics.descriptive.SumOfCubedDeviations
Copy constructor.
SumOfFourthDeviations - Class in org.apache.commons.statistics.descriptive
Computes the sum of fourth deviations from the sample mean.
SumOfFourthDeviations() - Constructor for class org.apache.commons.statistics.descriptive.SumOfFourthDeviations
Create an instance.
SumOfFourthDeviations(double, double, double, double, long) - Constructor for class org.apache.commons.statistics.descriptive.SumOfFourthDeviations
Create an instance with the given sum of cubed and squared deviations, and first moment.
SumOfFourthDeviations(double, SumOfCubedDeviations) - Constructor for class org.apache.commons.statistics.descriptive.SumOfFourthDeviations
Create an instance with the given sum of fourth and squared deviations.
sumOfLogs - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
The SumOfLogs constructor.
sumOfLogs - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics
The SumOfLogs implementation.
sumOfLogs - Variable in class org.apache.commons.statistics.descriptive.GeometricMean
Sum of logs used to compute the geometric mean.
sumOfLogs - Variable in class org.apache.commons.statistics.descriptive.IntStatistics.Builder
The SumOfLogs constructor.
sumOfLogs - Variable in class org.apache.commons.statistics.descriptive.IntStatistics
The SumOfLogs implementation.
sumOfLogs - Variable in class org.apache.commons.statistics.descriptive.LongStatistics.Builder
The SumOfLogs constructor.
sumOfLogs - Variable in class org.apache.commons.statistics.descriptive.LongStatistics
The SumOfLogs implementation.
SumOfLogs - Class in org.apache.commons.statistics.descriptive
Returns the sum of the natural logarithm of available values.
SumOfLogs() - Constructor for class org.apache.commons.statistics.descriptive.SumOfLogs
Create an instance.
SumOfSquaredDeviations - Class in org.apache.commons.statistics.descriptive
Computes the sum of squared deviations from the sample mean.
SumOfSquaredDeviations() - Constructor for class org.apache.commons.statistics.descriptive.SumOfSquaredDeviations
Create an instance.
SumOfSquaredDeviations(double, double, long) - Constructor for class org.apache.commons.statistics.descriptive.SumOfSquaredDeviations
Create an instance with the given sum of squared deviations and first moment.
SumOfSquaredDeviations(double, FirstMoment) - Constructor for class org.apache.commons.statistics.descriptive.SumOfSquaredDeviations
Create an instance with the given sum of squared deviations and first moment.
SumOfSquaredDeviations(SumOfSquaredDeviations) - Constructor for class org.apache.commons.statistics.descriptive.SumOfSquaredDeviations
Copy constructor.
sumOfSquares - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder
The SumOfSquares constructor.
sumOfSquares - Variable in class org.apache.commons.statistics.descriptive.DoubleStatistics
The SumOfSquares implementation.
sumOfSquares - Variable in class org.apache.commons.statistics.descriptive.IntStatistics.Builder
The IntSumOfSquares constructor.
sumOfSquares - Variable in class org.apache.commons.statistics.descriptive.IntStatistics
The IntSumOfSquares implementation.
sumOfSquares - Variable in class org.apache.commons.statistics.descriptive.LongStatistics.Builder
The LongSumOfSquares constructor.
sumOfSquares - Variable in class org.apache.commons.statistics.descriptive.LongStatistics
The LongSumOfSquares implementation.
SumOfSquares - Class in org.apache.commons.statistics.descriptive
Returns the sum of the squares of the available values.
SumOfSquares() - Constructor for class org.apache.commons.statistics.descriptive.SumOfSquares
Create an instance.
sumSq - Variable in class org.apache.commons.statistics.descriptive.IntStandardDeviation
Sum of the squared values.
sumSq - Variable in class org.apache.commons.statistics.descriptive.IntSumOfSquares
Sum of the squared values.
sumSq - Variable in class org.apache.commons.statistics.descriptive.IntVariance
Sum of the squared values.
sumSq - Variable in class org.apache.commons.statistics.descriptive.LongStandardDeviation
Sum of the squared values.
sumSq - Variable in class org.apache.commons.statistics.descriptive.LongSumOfSquares
Sum of the squared values.
sumSq - Variable in class org.apache.commons.statistics.descriptive.LongVariance
Sum of the squared values.
sumSquaredDev - Variable in class org.apache.commons.statistics.descriptive.SumOfSquaredDeviations
Sum of squared deviations of the values that have been added.
SUPPORT_HI - Static variable in class org.apache.commons.statistics.distribution.ExponentialDistribution
Support upper bound.
SUPPORT_HI - Static variable in class org.apache.commons.statistics.distribution.FDistribution
Support upper bound.
SUPPORT_HI - Static variable in class org.apache.commons.statistics.distribution.GammaDistribution
Support upper bound.
SUPPORT_HI - Static variable in class org.apache.commons.statistics.distribution.GumbelDistribution
Support upper bound.
SUPPORT_HI - Static variable in class org.apache.commons.statistics.distribution.LogisticDistribution
Support upper bound.
SUPPORT_HI - Static variable in class org.apache.commons.statistics.distribution.NakagamiDistribution
Support upper bound.
SUPPORT_HI - Static variable in class org.apache.commons.statistics.distribution.WeibullDistribution
Support upper bound.
SUPPORT_LO - Static variable in class org.apache.commons.statistics.distribution.ExponentialDistribution
Support lower bound.
SUPPORT_LO - Static variable in class org.apache.commons.statistics.distribution.FDistribution
Support lower bound.
SUPPORT_LO - Static variable in class org.apache.commons.statistics.distribution.GammaDistribution
Support lower bound.
SUPPORT_LO - Static variable in class org.apache.commons.statistics.distribution.GumbelDistribution
Support lower bound.
SUPPORT_LO - Static variable in class org.apache.commons.statistics.distribution.LogisticDistribution
Support lower bound.
SUPPORT_LO - Static variable in class org.apache.commons.statistics.distribution.NakagamiDistribution
Support lower bound.
SUPPORT_LO - Static variable in class org.apache.commons.statistics.distribution.WeibullDistribution
Support lower bound.
survivalProbability(double) - Method in class org.apache.commons.statistics.distribution.BetaDistribution
For a random variable X whose values are distributed according to this distribution, this method 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 org.apache.commons.statistics.distribution.DistributionException
Error message for "too large" condition when x > y.
TOO_SMALL - Static variable in exception org.apache.commons.statistics.distribution.DistributionException
Error message for "too small" condition when x < y.
TrapezoidalDistribution - Class in org.apache.commons.statistics.distribution
Implementation of the trapezoidal distribution.
TrapezoidalDistribution(double, double, double, double) - Constructor for class org.apache.commons.statistics.distribution.TrapezoidalDistribution
 
TrapezoidalDistribution.DelegatedTrapezoidalDistribution - Class in org.apache.commons.statistics.distribution
Specialisation of the trapezoidal distribution used when the distribution simplifies to an alternative distribution.
TrapezoidalDistribution.RegularTrapezoidalDistribution - Class in org.apache.commons.statistics.distribution
Regular implementation of the trapezoidal distribution.
TrapezoidalDistribution.TriangularTrapezoidalDistribution - Class in org.apache.commons.statistics.distribution
Specialisation of the trapezoidal distribution used when b == c.
TrapezoidalDistribution.UniformTrapezoidalDistribution - Class in org.apache.commons.statistics.distribution
Specialisation of the trapezoidal distribution used when a == b 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 org.apache.commons.statistics.inference.InferenceException
Error message for "categories x < 2".
TWO_PI - Static variable in class org.apache.commons.statistics.distribution.SaddlePointExpansionUtils
2 π.
TWO_POW_53 - Static variable in class org.apache.commons.statistics.descriptive.IntMath
2^53.
TWO_SIDED - org.apache.commons.statistics.inference.AlternativeHypothesis
Represents a two-sided test.
TWO_VALUES_REQUIRED - Static variable in exception org.apache.commons.statistics.inference.InferenceException
Error message for "values x < 2".
TwoResult(double, int, double, boolean, double, double) - Constructor for class org.apache.commons.statistics.inference.KolmogorovSmirnovTest.TwoResult
Create an instance.
twoSampleApproximateP(double, int, int, boolean) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
Uses the Kolmogorov-Smirnov distribution to approximate \(P(D_{n,m} > d)\) where \(D_{n,m}\) is the 2-sample Kolmogorov-Smirnov statistic.
twoSampleExactP(long, int, int, int, boolean, boolean) - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
Computes \(P(D_{n,m} > d)\) if strict 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 org.apache.commons.statistics.inference.InferenceException
Error message for "mismatch" condition when "values x != y".
VALUES_REQUIRED - Static variable in exception org.apache.commons.statistics.inference.InferenceException
Error message for "values x < y".
VAR - Static variable in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.HalfNormalDistribution
Variance constant (1 - 2/pi).
variance - Variable in class org.apache.commons.statistics.distribution.BetaDistribution
Cached value for inverse probability function.
variance - Variable in class org.apache.commons.statistics.distribution.FDistribution
Cached value for inverse probability function.
variance - Variable in class org.apache.commons.statistics.distribution.FoldedNormalDistribution.RegularFoldedNormalDistribution
Cached value for inverse probability function.
variance - Variable in class org.apache.commons.statistics.distribution.GammaDistribution
Cached value for inverse probability function.
variance - Variable in class org.apache.commons.statistics.distribution.NakagamiDistribution
Cached value for inverse probability function.
variance - Variable in class org.apache.commons.statistics.distribution.TDistribution.StudentsTDistribution
Cached value for inverse probability function.
variance(double, double) - Static method in class org.apache.commons.statistics.distribution.TruncatedNormalDistribution
Compute the variance of the truncated standard normal distribution.
Variance - Class in org.apache.commons.statistics.descriptive
Computes the variance of the available values.
Variance() - Constructor for class org.apache.commons.statistics.descriptive.Variance
Create an instance.
Variance(SumOfSquaredDeviations) - Constructor for class org.apache.commons.statistics.descriptive.Variance
Creates an instance with the sum of squared deviations from the mean.
VARIANCE - org.apache.commons.statistics.descriptive.Statistic
Variance.
varianceDifference(double[], double[], double) - Static method in class org.apache.commons.statistics.inference.StatisticUtils
Returns the variance of the (signed) differences between corresponding elements of the input arrays, or NaN if the arrays are empty.
VERY_LARGE_N - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution.One
"Very large" n to use a asymptotic limiting form.

W

WeibullDistribution - Class in org.apache.commons.statistics.distribution
Implementation of the Weibull distribution.
WeibullDistribution(double, double) - Constructor for class org.apache.commons.statistics.distribution.WeibullDistribution
 
width - Variable in class org.apache.commons.statistics.inference.UnconditionedExactTest.XYList
Width, or maximum x value (exclusive).
WilcoxonSignedRankTest - Class in org.apache.commons.statistics.inference
Implements the Wilcoxon signed-rank test.
WilcoxonSignedRankTest(AlternativeHypothesis, PValueMethod, boolean, double) - Constructor for class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
 
WilcoxonSignedRankTest.Result - Class in org.apache.commons.statistics.inference
Result for the Wilcoxon signed-rank test.
with(UniformRandomProvider) - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
Return an instance with the configured source of randomness.
with(NaNPolicy) - Method in class org.apache.commons.statistics.descriptive.Median
Return an instance with the configured NaNPolicy.
with(NaNPolicy) - Method in class org.apache.commons.statistics.descriptive.Quantile
Return an instance with the configured NaNPolicy.
with(Quantile.EstimationMethod) - Method in class org.apache.commons.statistics.descriptive.Quantile
Return an instance with the configured Quantile.EstimationMethod.
with(AlternativeHypothesis) - Method in class org.apache.commons.statistics.inference.BinomialTest
Return an instance with the configured alternative hypothesis.
with(AlternativeHypothesis) - Method in class org.apache.commons.statistics.inference.FisherExactTest
Return an instance with the configured alternative hypothesis.
with(AlternativeHypothesis) - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
Return an instance with the configured alternative hypothesis.
with(AlternativeHypothesis) - Method in class org.apache.commons.statistics.inference.MannWhitneyUTest
Return an instance with the configured alternative hypothesis.
with(AlternativeHypothesis) - Method in class org.apache.commons.statistics.inference.TTest
Return an instance with the configured alternative hypothesis.
with(AlternativeHypothesis) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest
Return an instance with the configured alternative hypothesis.
with(AlternativeHypothesis) - Method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
Return an instance with the configured alternative hypothesis.
with(ContinuityCorrection) - Method in class org.apache.commons.statistics.inference.MannWhitneyUTest
Return an instance with the configured continuity correction.
with(ContinuityCorrection) - Method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
Return an instance with the configured continuity correction.
with(DataDispersion) - Method in class org.apache.commons.statistics.inference.TTest
Return an instance with the configured assumption on the data dispersion.
with(Inequality) - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
Return an instance with the configured inequality.
with(PValueMethod) - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
Return an instance with the configured p-value method.
with(PValueMethod) - Method in class org.apache.commons.statistics.inference.MannWhitneyUTest
Return an instance with the configured p-value method.
with(PValueMethod) - Method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
Return an instance with the configured p-value method.
with(UnconditionedExactTest.Method) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest
Return an instance with the configured method.
withBiased(boolean) - Method in class org.apache.commons.statistics.descriptive.StatisticsConfiguration
Return an instance with the configured biased option.
withCopy(boolean) - Method in class org.apache.commons.statistics.descriptive.Median
Return an instance with the configured copy behaviour.
withCopy(boolean) - Method in class org.apache.commons.statistics.descriptive.Quantile
Return an instance with the configured copy behaviour.
withDefaults() - Static method in class org.apache.commons.statistics.descriptive.Median
Return a new instance with the default options.
withDefaults() - Static method in class org.apache.commons.statistics.descriptive.Quantile
Return a new instance with the default options.
withDefaults() - Static method in class org.apache.commons.statistics.descriptive.StatisticsConfiguration
Return an instance using the default options.
withDefaults() - Static method in class org.apache.commons.statistics.inference.BinomialTest
Return an instance using the default options.
withDefaults() - Static method in class org.apache.commons.statistics.inference.ChiSquareTest
Return an instance using the default options.
withDefaults() - Static method in class org.apache.commons.statistics.inference.FisherExactTest
Return an instance using the default options.
withDefaults() - Static method in class org.apache.commons.statistics.inference.GTest
Return an instance using the default options.
withDefaults() - Static method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
Return an instance using the default options.
withDefaults() - Static method in class org.apache.commons.statistics.inference.MannWhitneyUTest
Return an instance using the default options.
withDefaults() - Static method in class org.apache.commons.statistics.inference.OneWayAnova
Return an instance using the default options.
withDefaults() - Static method in class org.apache.commons.statistics.inference.TTest
Return an instance using the default options.
withDefaults() - Static method in class org.apache.commons.statistics.inference.UnconditionedExactTest
Return an instance using the default options.
withDefaults() - Static method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
Return an instance using the default options.
withDegreesOfFreedomAdjustment(int) - Method in class org.apache.commons.statistics.inference.ChiSquareTest
Return an instance with the configured degrees of freedom adjustment.
withDegreesOfFreedomAdjustment(int) - Method in class org.apache.commons.statistics.inference.GTest
Return an instance with the configured degrees of freedom adjustment.
withInitialPoints(int) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest
Return an instance with the configured number of initial points.
withIterations(int) - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest
Return an instance with the configured number of iterations.
withMu(double) - Method in class org.apache.commons.statistics.inference.MannWhitneyUTest
Return an instance with the configured location shift mu.
withMu(double) - Method in class org.apache.commons.statistics.inference.TTest
Return an instance with the configured mu.
withMu(double) - Method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest
Return an instance with the configured expected difference mu.
withOptimize(boolean) - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest
Return an instance with the configured optimization of initial search points.

X

X_GT_Y - Static variable in exception org.apache.commons.statistics.inference.InferenceException
Error message for "too large" condition when "x > y".
X_GTE_Y - Static variable in exception org.apache.commons.statistics.inference.InferenceException
Error message for "too large" condition when "x >= y".
X_KS_HALF - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution
Value of x when the KS sum is 0.5.
X_KS_ONE - Static variable in class org.apache.commons.statistics.inference.KolmogorovSmirnovDistribution
Value of x when the KS sum is 1.0.
X_LT_Y - Static variable in exception org.apache.commons.statistics.inference.InferenceException
Error message for "too small" condition when "x < y".
xsqrt2pi(double) - Static method in class org.apache.commons.statistics.distribution.ExtendedPrecision
Multiply the term by sqrt(2 pi).
XYList(int, int) - Constructor for class org.apache.commons.statistics.inference.UnconditionedExactTest.XYList
Create an instance.

Z

Z_POOLED - org.apache.commons.statistics.inference.UnconditionedExactTest.Method
Uses the test statistic from a Z-test using a pooled variance.
Z_UNPOOLED - org.apache.commons.statistics.inference.UnconditionedExactTest.Method
Uses the test statistic from a Z-test using an unpooled variance.
ZERO - Static variable in exception org.apache.commons.statistics.inference.InferenceException
Error message for "zero" condition when "x == 0".
ZERO_AT - Static variable in exception org.apache.commons.statistics.inference.InferenceException
Error message for "zero" condition when "x[i] == 0".
zeroValues - Variable in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest.Result
Flag indicating the data had zero values.
zeroVariance(double, double) - Static method in class org.apache.commons.statistics.descriptive.Statistics
Returns true if the second central 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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