Index (Apache Commons Statistics 1.2 API)

A B C D E F G H I J K L M N O P Q R S T U V W Z
All Classes and Interfaces|All Packages

A

a - Variable in class org.apache.commons.statistics.distribution.TrapezoidalDistribution: Lower limit of this distribution (inclusive).
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.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.SumOfLogs: 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.
AGRESTI_COULL - Enum constant in enum org.apache.commons.statistics.interval.BinomialConfidenceInterval: Implements the Agresti-Coull method for creating a binomial proportion confidence interval.
AlternativeHypothesis - Enum in org.apache.commons.statistics.inference: Represents an alternative hypothesis for a hypothesis test.
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.
ASYMPTOTIC - Enum constant in enum org.apache.commons.statistics.inference.PValueMethod: Use the asymptotic distribution of the test statistic to evaluate the p-value.
AUTO - Enum constant in enum org.apache.commons.statistics.inference.PValueMethod: Automatically choose the method to evaluate the p-value.
AVERAGE - Enum constant in enum org.apache.commons.statistics.ranking.TiesStrategy: Tied values are assigned the average of the applicable ranks.

B

b - Variable in class org.apache.commons.statistics.distribution.TrapezoidalDistribution: Start of the trapezoid constant density.
BetaDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the beta distribution.
BinomialConfidenceInterval - Enum in org.apache.commons.statistics.interval: Generate confidence intervals for a binomial proportion.
BinomialDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the binomial distribution.
BinomialTest - Class in org.apache.commons.statistics.inference: Implements binomial test statistics.
BOSCHLOO - Enum constant in enum org.apache.commons.statistics.inference.UnconditionedExactTest.Method: Uses the p-value from Fisher's exact test.
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 an 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(double[], int, int) - Method in class org.apache.commons.statistics.descriptive.DoubleStatistics.Builder: Builds a DoubleStatistics instance using the specified range of values.
build(int...) - Method in class org.apache.commons.statistics.descriptive.IntStatistics.Builder: Builds an IntStatistics instance using the input values.
build(int[], int, int) - Method in class org.apache.commons.statistics.descriptive.IntStatistics.Builder: Builds an IntStatistics instance using the specified range of values.
build(long...) - Method in class org.apache.commons.statistics.descriptive.LongStatistics.Builder: Builds a LongStatistics instance using the input values.
build(long[], int, int) - Method in class org.apache.commons.statistics.descriptive.LongStatistics.Builder: Builds a LongStatistics instance using the specified range of 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.

C

c - Variable in class org.apache.commons.statistics.distribution.TrapezoidalDistribution: End of the trapezoid constant density.
CauchyDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the Cauchy distribution.
ChiSquaredDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the chi-squared distribution.
ChiSquareTest - Class in org.apache.commons.statistics.inference: Implements chi-square test statistics.
CLOPPER_PEARSON - Enum constant in enum org.apache.commons.statistics.interval.BinomialConfidenceInterval: Implements the Clopper-Pearson method for creating a binomial proportion confidence interval.
combine(DoubleStatistics) - Method in class org.apache.commons.statistics.descriptive.DoubleStatistics: Combines the state of the other statistics 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(SumOfLogs) - Method in class org.apache.commons.statistics.descriptive.SumOfLogs
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.
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.
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.
create() - Static method in class org.apache.commons.statistics.descriptive.GeometricMean: Creates 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.Variance: Creates an instance.
createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.FDistribution: Creates a sampler.
createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution: Creates a sampler.
createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.GumbelDistribution: Creates a sampler.
createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.LaplaceDistribution: Creates a sampler.
createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.LogisticDistribution: Creates a sampler.
createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.TDistribution: Creates a sampler.
createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution: Creates a sampler.
createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.TriangularDistribution: Creates a sampler.
createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.BinomialDistribution: Creates a sampler.
createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution: Creates a sampler.
createSampler(UniformRandomProvider) - Method in class org.apache.commons.statistics.distribution.PascalDistribution: 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.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.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.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.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.distribution.TrapezoidalDistribution: Upper limit of this distribution (inclusive).
DataDispersion - Enum in org.apache.commons.statistics.inference: Represents an assumption on the dispersion of data.
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.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.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.
DISABLED - Enum constant in enum org.apache.commons.statistics.inference.ContinuityCorrection: Disable continuity correction.
DiscreteDistribution - Interface in org.apache.commons.statistics.distribution: Interface for distributions on the integers.
DiscreteDistribution.Sampler - Interface in org.apache.commons.statistics.distribution: Distribution sampling functionality.
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.Builder - Class in org.apache.commons.statistics.descriptive: A builder for DoubleStatistics.

E

ENABLED - Enum constant in enum org.apache.commons.statistics.inference.ContinuityCorrection: Enable continuity correction.
ERROR - Enum constant in enum org.apache.commons.statistics.descriptive.NaNPolicy: NaNs result in an exception.
ESTIMATE - Enum constant in enum org.apache.commons.statistics.inference.PValueMethod: Use an estimation method for the p-value.
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.
evaluateRange(double[], int, int) - Method in class org.apache.commons.statistics.descriptive.Median: Evaluate the median of the specified range.
evaluateRange(double[], int, int, double) - Method in class org.apache.commons.statistics.descriptive.Quantile: Evaluate the p-th quantile of the specified range of values.
evaluateRange(double[], int, int, double...) - Method in class org.apache.commons.statistics.descriptive.Quantile: Evaluate the p-th quantiles of the specified range of values.
evaluateRange(int[], int, int) - Method in class org.apache.commons.statistics.descriptive.Median: Evaluate the median of the specified range.
evaluateRange(int[], int, int, double) - Method in class org.apache.commons.statistics.descriptive.Quantile: Evaluate the p-th quantile of the specified range of values.
evaluateRange(int[], int, int, double...) - Method in class org.apache.commons.statistics.descriptive.Quantile: Evaluate the p-th quantiles of the specified range of values..
EXACT - Enum constant in enum org.apache.commons.statistics.inference.PValueMethod: Use the exact distribution of the test statistic to evaluate the p-value.
EXCLUDE - Enum constant in enum org.apache.commons.statistics.descriptive.NaNPolicy: NaNs are excluded from the data.
ExponentialDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the exponential distribution.

F

FAILED - Enum constant in enum org.apache.commons.statistics.ranking.NaNStrategy: NaNs result in an exception.
FDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the F-distribution.
FisherExactTest - Class in org.apache.commons.statistics.inference: Implements Fisher's exact test.
FIXED - Enum constant in enum org.apache.commons.statistics.ranking.NaNStrategy: NaNs are left fixed "in place", that is the rank transformation is applied to the other elements in the input array, but the NaN elements are returned unchanged.
FoldedNormalDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the folded normal distribution.
fromErrorRate(double, double, long, double) - Method in enum org.apache.commons.statistics.interval.NormalConfidenceInterval: Create a confidence interval from an independent sample from an unknown normally distributed population with the given error rate.
fromErrorRate(int, int, double) - Method in enum org.apache.commons.statistics.interval.BinomialConfidenceInterval: Create a confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and error rate.

G

GammaDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the gamma distribution.
GEOMETRIC_MEAN - Enum constant in enum org.apache.commons.statistics.descriptive.Statistic: Geometric mean.
GeometricDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the geometric distribution.
GeometricMean - Class in org.apache.commons.statistics.descriptive: Computes the geometric mean of the available values.
getAlpha() - Method in class org.apache.commons.statistics.distribution.BetaDistribution: Gets the first shape parameter of this distribution.
getAsBigInteger() - Method in class org.apache.commons.statistics.descriptive.IntMax
getAsBigInteger() - Method in class org.apache.commons.statistics.descriptive.IntMin
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 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 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 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 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 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 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 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 class org.apache.commons.statistics.descriptive.IntMax
getAsLong() - Method in class org.apache.commons.statistics.descriptive.IntMin
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 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.
getExponent() - Method in class org.apache.commons.statistics.distribution.ZipfDistribution: Gets the exponent parameter of this distribution.
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.
getLowerBound() - Method in interface org.apache.commons.statistics.interval.Interval: Get the lower bound of the interval.
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.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.TrapezoidalDistribution: Gets the mean of this distribution.
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.
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.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.
getPopulationSize() - Method in class org.apache.commons.statistics.distribution.HypergeometricDistribution: Gets the population size parameter of this distribution.
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.KolmogorovSmirnovTest.OneResult
getPValue() - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest.TwoResult
getPValue() - Method in class org.apache.commons.statistics.inference.MannWhitneyUTest.Result
getPValue() - Method in class org.apache.commons.statistics.inference.OneWayAnova.Result
getPValue() - Method in class org.apache.commons.statistics.inference.TTest.Result
getPValue() - Method in class org.apache.commons.statistics.inference.UnconditionedExactTest.Result
getPValue() - Method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest.Result
getPValue() - Method in interface org.apache.commons.statistics.inference.SignificanceResult: Returns the test statistic p-value.
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.
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.
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.KolmogorovSmirnovTest.OneResult
getStatistic() - Method in class org.apache.commons.statistics.inference.OneWayAnova.Result
getStatistic() - Method in class org.apache.commons.statistics.inference.TTest.Result
getStatistic() - Method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest.Result
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.
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.
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.
getTiesStrategy() - Method in class org.apache.commons.statistics.ranking.NaturalRanking: Return the TiesStrategy.
getUpperBound() - Method in interface org.apache.commons.statistics.interval.Interval: Get the upper bound of the interval.
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.
getUpperPValue() - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest.TwoResult: Return the p-value of the upper bound of the D statistic.
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.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.TrapezoidalDistribution: Gets the variance of this distribution.
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.
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.
GREATER_THAN - Enum constant in enum org.apache.commons.statistics.inference.AlternativeHypothesis: Represents a right-sided test.
GTest - Class in org.apache.commons.statistics.inference: Implements G-test (Generalized Log-Likelihood Ratio Test) statistics.
GumbelDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the Gumbel distribution.

H

hasSignificantTies() - Method in class org.apache.commons.statistics.inference.KolmogorovSmirnovTest.TwoResult: Returns true if there were ties between samples that occurred in a region which could change the D statistic if the ties were resolved to a defined order.
hasTiedValues() - Method in class org.apache.commons.statistics.inference.MannWhitneyUTest.Result: Return true if the data had tied values.
hasTiedValues() - Method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest.Result: Return true if the data had tied values (with equal ranks).
hasZeroValues() - Method in class org.apache.commons.statistics.inference.WilcoxonSignedRankTest.Result: Return true if the data had zero values.
HETEROSCEDASTIC - Enum constant in enum org.apache.commons.statistics.inference.DataDispersion: Data does not have the same variance.
HF1 - Enum constant in enum org.apache.commons.statistics.descriptive.Quantile.EstimationMethod: Inverse of the empirical distribution function.
HF2 - Enum constant in enum org.apache.commons.statistics.descriptive.Quantile.EstimationMethod: Similar to Quantile.EstimationMethod.HF1 with averaging at discontinuities.
HF3 - Enum constant in enum org.apache.commons.statistics.descriptive.Quantile.EstimationMethod: The observation closest to \( np \).
HF4 - Enum constant in enum org.apache.commons.statistics.descriptive.Quantile.EstimationMethod: Linear interpolation of the inverse of the empirical CDF.
HF5 - Enum constant in enum org.apache.commons.statistics.descriptive.Quantile.EstimationMethod: A piecewise linear function where the knots are the values midway through the steps of the empirical CDF.
HF6 - Enum constant in enum org.apache.commons.statistics.descriptive.Quantile.EstimationMethod: Linear interpolation of the expectations for the order statistics for the uniform distribution on [0,1].
HF7 - Enum constant in enum org.apache.commons.statistics.descriptive.Quantile.EstimationMethod: Linear interpolation of the modes for the order statistics for the uniform distribution on [0,1].
HF8 - Enum constant in enum org.apache.commons.statistics.descriptive.Quantile.EstimationMethod: Linear interpolation of the approximate medians for order statistics.
HF9 - Enum constant in enum org.apache.commons.statistics.descriptive.Quantile.EstimationMethod: Quantile estimates are approximately unbiased for the expected order statistics if \( x \) is normally distributed.
HOMOSCEDASTIC - Enum constant in enum org.apache.commons.statistics.inference.DataDispersion: All data has the same finite variance (homogeneity of variance).
HypergeometricDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the hypergeometric distribution.

I

INCLUDE - Enum constant in enum org.apache.commons.statistics.descriptive.NaNPolicy: NaNs are included in the data.
Inequality - Enum in org.apache.commons.statistics.inference: Represents a non-equal comparison between two numbers.
Interval - Interface in org.apache.commons.statistics.interval: Interface representing an interval.
IntMax - Class in org.apache.commons.statistics.descriptive: Returns the maximum of the available values.
IntMean - Class in org.apache.commons.statistics.descriptive: Computes the arithmetic mean of the available values.
IntMin - Class in org.apache.commons.statistics.descriptive: Returns the minimum of the available values.
IntStandardDeviation - Class in org.apache.commons.statistics.descriptive: Computes the standard deviation of the available values.
IntStatistic - Interface in org.apache.commons.statistics.descriptive: Represents a state object for computing a statistic over int valued input(s).
IntStatistics - Class in org.apache.commons.statistics.descriptive: Statistics for int values.
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.
IntSumOfSquares - Class in org.apache.commons.statistics.descriptive: Returns the sum of the squares of the available values.
IntVariance - Class in org.apache.commons.statistics.descriptive: Computes the variance of the available values.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.BetaDistribution: Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.FDistribution: Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution: Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.GammaDistribution: Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.NakagamiDistribution: Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.TDistribution: Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution: Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.BinomialDistribution: Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.PascalDistribution: Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.PoissonDistribution: Computes the quantile function of this distribution.
inverseCumulativeProbability(double) - Method in class org.apache.commons.statistics.distribution.ZipfDistribution: 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.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.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.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.BetaDistribution: Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.FDistribution: Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.FoldedNormalDistribution: Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.GammaDistribution: Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.NakagamiDistribution: Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.TrapezoidalDistribution: Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.BinomialDistribution: Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.PascalDistribution: Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.PoissonDistribution: Computes the inverse survival probability function of this distribution.
inverseSurvivalProbability(double) - Method in class org.apache.commons.statistics.distribution.ZipfDistribution: 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.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.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.
isBiased() - Method in class org.apache.commons.statistics.descriptive.StatisticsConfiguration: Checks if the calculation of the statistic is biased.
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.

J

JEFFREYS - Enum constant in enum org.apache.commons.statistics.interval.BinomialConfidenceInterval: Implements the Jeffreys method for creating a binomial proportion confidence interval.

K

KolmogorovSmirnovTest - Class in org.apache.commons.statistics.inference: Implements the Kolmogorov-Smirnov (K-S) test for equality of continuous distributions.
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.
Kurtosis - Class in org.apache.commons.statistics.descriptive: Computes the kurtosis of the available values.
KURTOSIS - Enum constant in enum org.apache.commons.statistics.descriptive.Statistic: Kurtosis.

L

LaplaceDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the Laplace distribution.
LESS_THAN - Enum constant in enum org.apache.commons.statistics.inference.AlternativeHypothesis: Represents a left-sided test.
LevyDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the Lévy distribution.
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.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.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.
LogisticDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the logistic distribution.
LogNormalDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the log-normal distribution.
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.
LogUniformDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the log-uniform distribution.
LongMax - Class in org.apache.commons.statistics.descriptive: Returns the maximum of the available values.
LongMean - Class in org.apache.commons.statistics.descriptive: Computes the arithmetic mean of the available values.
LongMin - Class in org.apache.commons.statistics.descriptive: Returns the minimum of the available values.
LongStandardDeviation - Class in org.apache.commons.statistics.descriptive: Computes the standard deviation of the available values.
LongStatistic - Interface in org.apache.commons.statistics.descriptive: Represents a state object for computing a statistic over long valued input(s).
LongStatistics - Class in org.apache.commons.statistics.descriptive: Statistics for long values.
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.
LongSumOfSquares - Class in org.apache.commons.statistics.descriptive: Returns the sum of the squares of the available values.
LongVariance - Class in org.apache.commons.statistics.descriptive: Computes the variance of the available values.

M

MannWhitneyUTest - Class in org.apache.commons.statistics.inference: Implements the Mann-Whitney U test (also called Wilcoxon rank-sum test).
MannWhitneyUTest.Result - Class in org.apache.commons.statistics.inference: Result for the Mann-Whitney U test.
Max - Class in org.apache.commons.statistics.descriptive: Returns the maximum of the available values.
MAX - Enum constant in enum org.apache.commons.statistics.descriptive.Statistic: Maximum.
MAXIMAL - Enum constant in enum org.apache.commons.statistics.ranking.NaNStrategy: NaNs are considered maximal in the ordering, equivalent to (that is, tied with) positive infinity.
MAXIMUM - Enum constant in enum org.apache.commons.statistics.ranking.TiesStrategy: Tied values are assigned the maximum applicable rank, or the rank of the last occurrence.
Mean - Class in org.apache.commons.statistics.descriptive: Computes the arithmetic mean of the available values.
MEAN - Enum constant in enum org.apache.commons.statistics.descriptive.Statistic: Mean, or average.
MEAN - Enum constant in enum org.apache.commons.statistics.interval.NormalConfidenceInterval: Create a confidence interval for the true mean of an unknown normally distributed population.
Median - Class in org.apache.commons.statistics.descriptive: Returns the median of the available values.
Min - Class in org.apache.commons.statistics.descriptive: Returns the minimum of the available values.
MIN - Enum constant in enum org.apache.commons.statistics.descriptive.Statistic: Minimum.
MINIMAL - Enum constant in enum org.apache.commons.statistics.ranking.NaNStrategy: NaNs are considered minimal in the ordering, equivalent to (that is, tied with) negative infinity.
MINIMUM - Enum constant in enum org.apache.commons.statistics.ranking.TiesStrategy: Tied values are assigned the minimum applicable rank, or the rank of the first occurrence.

N

NakagamiDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the Nakagami distribution.
NaNPolicy - Enum in org.apache.commons.statistics.descriptive: Defines the policy for NaN values found in data.
NaNStrategy - Enum in org.apache.commons.statistics.ranking: Strategies for handling NaN values in rank transformations.
NaturalRanking - Class in org.apache.commons.statistics.ranking: Ranking based on the natural ordering on floating-point values.
NaturalRanking() - Constructor for class org.apache.commons.statistics.ranking.NaturalRanking: Creates an instance with NaNStrategy.FAILED and TiesStrategy.AVERAGE.
NaturalRanking(IntUnaryOperator) - Constructor for class org.apache.commons.statistics.ranking.NaturalRanking: Creates an instance with NaNStrategy.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(TiesStrategy) - Constructor for class org.apache.commons.statistics.ranking.NaturalRanking: Creates an instance with NaNStrategy.FAILED and the specified @tiesStrategy.
NON_STRICT - Enum constant in enum org.apache.commons.statistics.inference.Inequality: Represents a non-strict inequality (numbers may be equal).
NORMAL_APPROXIMATION - Enum constant in enum org.apache.commons.statistics.interval.BinomialConfidenceInterval: Implements the normal approximation method for creating a binomial proportion confidence interval.
NormalConfidenceInterval - Enum in org.apache.commons.statistics.interval: Generate confidence intervals for a normally distributed population.
NormalDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the normal (Gaussian) distribution.

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.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.SumOfLogs: 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, 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.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.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.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.
ofRange(double[], int, int) - Static method in class org.apache.commons.statistics.descriptive.GeometricMean: Returns an instance populated using the specified range of values.
ofRange(double[], int, int) - Static method in class org.apache.commons.statistics.descriptive.Kurtosis: Returns an instance populated using the specified range of values.
ofRange(double[], int, int) - Static method in class org.apache.commons.statistics.descriptive.Max: Returns an instance populated using the specified range of values.
ofRange(double[], int, int) - Static method in class org.apache.commons.statistics.descriptive.Mean: Returns an instance populated using the specified range of values.
ofRange(double[], int, int) - Static method in class org.apache.commons.statistics.descriptive.Min: Returns an instance populated using the specified range of values.
ofRange(double[], int, int) - Static method in class org.apache.commons.statistics.descriptive.Product: Returns an instance populated using the specified range of values.
ofRange(double[], int, int) - Static method in class org.apache.commons.statistics.descriptive.Skewness: Returns an instance populated using the specified range of values.
ofRange(double[], int, int) - Static method in class org.apache.commons.statistics.descriptive.StandardDeviation: Returns an instance populated using the specified range of values.
ofRange(double[], int, int) - Static method in class org.apache.commons.statistics.descriptive.Sum: Returns an instance populated using the specified range of values.
ofRange(double[], int, int) - Static method in class org.apache.commons.statistics.descriptive.SumOfLogs: Returns an instance populated using the specified range of values.
ofRange(double[], int, int) - Static method in class org.apache.commons.statistics.descriptive.SumOfSquares: Returns an instance populated using the specified range of values.
ofRange(double[], int, int) - Static method in class org.apache.commons.statistics.descriptive.Variance: Returns an instance populated using the specified range of values.
ofRange(int[], int, int) - Static method in class org.apache.commons.statistics.descriptive.GeometricMean: Returns an instance populated using the specified range of values.
ofRange(int[], int, int) - Static method in class org.apache.commons.statistics.descriptive.IntMax: Returns an instance populated using the specified range of values.
ofRange(int[], int, int) - Static method in class org.apache.commons.statistics.descriptive.IntMean: Returns an instance populated using the specified range of values.
ofRange(int[], int, int) - Static method in class org.apache.commons.statistics.descriptive.IntMin: Returns an instance populated using the specified range of values.
ofRange(int[], int, int) - Static method in class org.apache.commons.statistics.descriptive.IntStandardDeviation: Returns an instance populated using the specified range of values.
ofRange(int[], int, int) - Static method in class org.apache.commons.statistics.descriptive.IntSum: Returns an instance populated using the specified range of values.
ofRange(int[], int, int) - Static method in class org.apache.commons.statistics.descriptive.IntSumOfSquares: Returns an instance populated using the specified range of values.
ofRange(int[], int, int) - Static method in class org.apache.commons.statistics.descriptive.IntVariance: Returns an instance populated using the specified range of values.
ofRange(int[], int, int) - Static method in class org.apache.commons.statistics.descriptive.Kurtosis: Returns an instance populated using the specified range of values.
ofRange(int[], int, int) - Static method in class org.apache.commons.statistics.descriptive.Product: Returns an instance populated using the specified range of values.
ofRange(int[], int, int) - Static method in class org.apache.commons.statistics.descriptive.Skewness: Returns an instance populated using the specified range of values.
ofRange(int[], int, int) - Static method in class org.apache.commons.statistics.descriptive.SumOfLogs: Returns an instance populated using the specified range of values.
ofRange(long[], int, int) - Static method in class org.apache.commons.statistics.descriptive.GeometricMean: Returns an instance populated using the specified range of values.
ofRange(long[], int, int) - Static method in class org.apache.commons.statistics.descriptive.Kurtosis: Returns an instance populated using the specified range of values.
ofRange(long[], int, int) - Static method in class org.apache.commons.statistics.descriptive.LongMax: Returns an instance populated using the specified range of values.
ofRange(long[], int, int) - Static method in class org.apache.commons.statistics.descriptive.LongMean: Returns an instance populated using the specified range of values.
ofRange(long[], int, int) - Static method in class org.apache.commons.statistics.descriptive.LongMin: Returns an instance populated using the specified range of values.
ofRange(long[], int, int) - Static method in class org.apache.commons.statistics.descriptive.LongStandardDeviation: Returns an instance populated using the specified range of values.
ofRange(long[], int, int) - Static method in class org.apache.commons.statistics.descriptive.LongSum: Returns an instance populated using the specified range of values.
ofRange(long[], int, int) - Static method in class org.apache.commons.statistics.descriptive.LongSumOfSquares: Returns an instance populated using the specified range of values.
ofRange(long[], int, int) - Static method in class org.apache.commons.statistics.descriptive.LongVariance: Returns an instance populated using the specified range of values.
ofRange(long[], int, int) - Static method in class org.apache.commons.statistics.descriptive.Product: Returns an instance populated using the specified range of values.
ofRange(long[], int, int) - Static method in class org.apache.commons.statistics.descriptive.Skewness: Returns an instance populated using the specified range of values.
ofRange(long[], int, int) - Static method in class org.apache.commons.statistics.descriptive.SumOfLogs: Returns an instance populated using the specified range of values.
ofRange(Set<Statistic>, double[], int, int) - Static method in class org.apache.commons.statistics.descriptive.DoubleStatistics: Returns a new instance configured to compute the specified statistics populated using the specified range of values.
ofRange(Set<Statistic>, int[], int, int) - Static method in class org.apache.commons.statistics.descriptive.IntStatistics: Returns a new instance configured to compute the specified statistics populated using the specified range of values.
ofRange(Set<Statistic>, long[], int, int) - Static method in class org.apache.commons.statistics.descriptive.LongStatistics: Returns a new instance configured to compute the specified statistics populated using the specified range of values.
OneWayAnova - Class in org.apache.commons.statistics.inference: Implements one-way ANOVA (analysis of variance) statistics.
OneWayAnova.Result - Class in org.apache.commons.statistics.inference: Result for the one-way ANOVA.
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.interval - package org.apache.commons.statistics.interval: Classes providing statistical intervals.
org.apache.commons.statistics.ranking - package org.apache.commons.statistics.ranking: Classes providing rank transformations.

P

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.
ParetoDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the Pareto (Type I) distribution.
PascalDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the Pascal distribution.
PoissonDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the Poisson distribution.
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.BetaDistribution: 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.CauchyDistribution: 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.ChiSquaredDistribution: 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.ExponentialDistribution: 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.FDistribution: 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: 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.GammaDistribution: 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.GumbelDistribution: 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.LaplaceDistribution: 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.LevyDistribution: 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.LogisticDistribution: 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.LogUniformDistribution: 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.NakagamiDistribution: 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.ParetoDistribution: 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: 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.TrapezoidalDistribution: 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.TriangularDistribution: 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.WeibullDistribution: 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.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.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.BinomialDistribution: 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.GeometricDistribution: 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.PascalDistribution: 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.PoissonDistribution: 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.ZipfDistribution: 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).
Product - Class in org.apache.commons.statistics.descriptive: Returns the product of the available values.
PRODUCT - Enum constant in enum org.apache.commons.statistics.descriptive.Statistic: Product.
PValueMethod - Enum in org.apache.commons.statistics.inference: Represents a method for computing a p-value for a test statistic.

Q

Quantile - Class in org.apache.commons.statistics.descriptive: Provides quantile computation.
Quantile.EstimationMethod - Enum in org.apache.commons.statistics.descriptive: Estimation methods for a quantile.

R

RANDOM - Enum constant in enum org.apache.commons.statistics.ranking.TiesStrategy: Tied values are assigned a unique random integral rank from among the applicable values.
RankingAlgorithm - Interface in org.apache.commons.statistics.ranking: Interface representing a rank transformation.
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.
REMOVED - Enum constant in enum org.apache.commons.statistics.ranking.NaNStrategy: NaNs are removed before rank transform is applied.

S

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.
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.
SEQUENTIAL - Enum constant in enum org.apache.commons.statistics.ranking.TiesStrategy: Ties are assigned ranks in order of occurrence in the original array.
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.
SignificanceResult - Interface in org.apache.commons.statistics.inference: Contains the result of a test for significance.
Skewness - Class in org.apache.commons.statistics.descriptive: Computes the skewness of the available values.
SKEWNESS - Enum constant in enum org.apache.commons.statistics.descriptive.Statistic: Skewness.
STANDARD_DEVIATION - Enum constant in enum org.apache.commons.statistics.descriptive.Statistic: Standard deviation.
StandardDeviation - Class in org.apache.commons.statistics.descriptive: Computes the standard deviation of the available values.
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.
StatisticAccumulator<T> - Interface in org.apache.commons.statistics.descriptive: A mutable result container that accumulates a StatisticResult.
StatisticResult - Interface in org.apache.commons.statistics.descriptive: Represents the result of a statistic computed over a set of values.
StatisticsConfiguration - Class in org.apache.commons.statistics.descriptive: Configuration for computation of statistics.
STRICT - Enum constant in enum org.apache.commons.statistics.inference.Inequality: Represents a strict inequality.
Sum - Class in org.apache.commons.statistics.descriptive: Returns the sum of the available values.
SUM - Enum constant in enum org.apache.commons.statistics.descriptive.Statistic: Sum.
SUM_OF_LOGS - Enum constant in enum org.apache.commons.statistics.descriptive.Statistic: Sum of the natural logarithm of values.
SUM_OF_SQUARES - Enum constant in enum org.apache.commons.statistics.descriptive.Statistic: Sum of the squared values.
SumOfLogs - Class in org.apache.commons.statistics.descriptive: Returns the sum of the natural logarithm of available values.
SumOfSquares - Class in org.apache.commons.statistics.descriptive: Returns the sum of the squares of the available values.
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.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.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).

T

TDistribution - 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.
TiesStrategy - Enum in org.apache.commons.statistics.ranking: Strategies for handling tied values in rank transformations.
TrapezoidalDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the trapezoidal distribution.
TriangularDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the triangular distribution.
TruncatedNormalDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the truncated normal distribution.
TTest - Class in org.apache.commons.statistics.inference: Implements Student's t-test statistics.
TTest.Result - Class in org.apache.commons.statistics.inference: Result for the t-test.
TWO_SIDED - Enum constant in enum org.apache.commons.statistics.inference.AlternativeHypothesis: Represents a two-sided test.

U

UnconditionedExactTest - Class in org.apache.commons.statistics.inference: Implements an unconditioned exact test for a contingency table.
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.
UniformContinuousDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the uniform distribution.
UniformDiscreteDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the uniform discrete distribution.

V

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.interval.BinomialConfidenceInterval: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.commons.statistics.interval.NormalConfidenceInterval: 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.interval.BinomialConfidenceInterval: 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.interval.NormalConfidenceInterval: 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.
Variance - Class in org.apache.commons.statistics.descriptive: Computes the variance of the available values.
VARIANCE - Enum constant in enum org.apache.commons.statistics.descriptive.Statistic: Variance.
VARIANCE - Enum constant in enum org.apache.commons.statistics.interval.NormalConfidenceInterval: Create a confidence interval for the true variance of an unknown normally distributed population.

W

WeibullDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the Weibull distribution.
WilcoxonSignedRankTest - Class in org.apache.commons.statistics.inference: Implements the Wilcoxon signed-rank test.
WilcoxonSignedRankTest.Result - Class in org.apache.commons.statistics.inference: Result for the Wilcoxon signed-rank test.
WILSON_SCORE - Enum constant in enum org.apache.commons.statistics.interval.BinomialConfidenceInterval: Implements the Wilson score method for creating a binomial proportion confidence interval.
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.

Z

Z_POOLED - Enum constant in enum org.apache.commons.statistics.inference.UnconditionedExactTest.Method: Uses the test statistic from a Z-test using a pooled variance.
Z_UNPOOLED - Enum constant in enum org.apache.commons.statistics.inference.UnconditionedExactTest.Method: Uses the test statistic from a Z-test using an unpooled variance.
ZipfDistribution - Class in org.apache.commons.statistics.distribution: Implementation of the Zipf distribution.

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