Uses of Interface
org.apache.commons.math3.distribution.RealDistribution
Packages that use RealDistribution
Package
Description
Implementations of common discrete and continuous distributions.
Neural networks.
Random number and random data generators.
Classes providing hypothesis testing.
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Uses of RealDistribution in org.apache.commons.math3.distribution
Classes in org.apache.commons.math3.distribution that implement RealDistributionModifier and TypeClassDescriptionclassBase class for probability distributions on the reals.classImplements the Beta distribution.classImplementation of the Cauchy distribution.classImplementation of the chi-squared distribution.classImplementation of the constant real distribution.classImplementation of a real-valuedEnumeratedDistribution.classImplementation of the exponential distribution.classImplementation of the F-distribution.classImplementation of the Gamma distribution.classThis class implements the Gumbel distribution.classThis class implements the Laplace distribution.classThis class implements the Lévy distribution.classThis class implements the Logistic distribution.classImplementation of the log-normal (gaussian) distribution.classThis class implements the Nakagami distribution.classImplementation of the normal (gaussian) distribution.classImplementation of the Pareto distribution.classImplementation of Student's t-distribution.classImplementation of the triangular real distribution.classImplementation of the uniform real distribution.classImplementation of the Weibull distribution. -
Uses of RealDistribution in org.apache.commons.math3.ml.neuralnet
Methods in org.apache.commons.math3.ml.neuralnet with parameters of type RealDistributionModifier and TypeMethodDescriptionstatic FeatureInitializerFeatureInitializerFactory.randomize(RealDistribution random, FeatureInitializer orig) Adds some amount of random data to the given initializer. -
Uses of RealDistribution in org.apache.commons.math3.random
Classes in org.apache.commons.math3.random that implement RealDistributionModifier and TypeClassDescriptionclassRepresents an empirical probability distribution -- a probability distribution derived from observed data without making any assumptions about the functional form of the population distribution that the data come from.Methods in org.apache.commons.math3.random that return RealDistributionModifier and TypeMethodDescriptionprotected RealDistributionEmpiricalDistribution.getKernel(SummaryStatistics bStats) The within-bin smoothing kernel.Methods in org.apache.commons.math3.random with parameters of type RealDistributionModifier and TypeMethodDescriptiondoubleRandomDataImpl.nextInversionDeviate(RealDistribution distribution) Deprecated.use the distribution's sample() method -
Uses of RealDistribution in org.apache.commons.math3.stat.inference
Methods in org.apache.commons.math3.stat.inference with parameters of type RealDistributionModifier and TypeMethodDescriptiondoubleKolmogorovSmirnovTest.kolmogorovSmirnovStatistic(RealDistribution distribution, double[] data) Computes the one-sample Kolmogorov-Smirnov test statistic, \(D_n=\sup_x |F_n(x)-F(x)|\) where \(F\) is the distribution (cdf) function associated withdistribution, \(n\) is the length ofdataand \(F_n\) is the empirical distribution that puts mass \(1/n\) at each of the values indata.static doubleTestUtils.kolmogorovSmirnovStatistic(RealDistribution dist, double[] data) doubleKolmogorovSmirnovTest.kolmogorovSmirnovTest(RealDistribution distribution, double[] data) Computes the p-value, or observed significance level, of a one-sample Kolmogorov-Smirnov test evaluating the null hypothesis thatdataconforms todistribution.doubleKolmogorovSmirnovTest.kolmogorovSmirnovTest(RealDistribution distribution, double[] data, boolean exact) Computes the p-value, or observed significance level, of a one-sample Kolmogorov-Smirnov test evaluating the null hypothesis thatdataconforms todistribution.booleanKolmogorovSmirnovTest.kolmogorovSmirnovTest(RealDistribution distribution, double[] data, double alpha) Performs a Kolmogorov-Smirnov test evaluating the null hypothesis thatdataconforms todistribution.static doubleTestUtils.kolmogorovSmirnovTest(RealDistribution dist, double[] data) static doubleTestUtils.kolmogorovSmirnovTest(RealDistribution dist, double[] data, boolean strict) static booleanTestUtils.kolmogorovSmirnovTest(RealDistribution dist, double[] data, double alpha)