| Package | Description | 
|---|---|
| org.apache.commons.math3.distribution | Implementations of common discrete and continuous distributions. | 
| org.apache.commons.math3.ml.neuralnet | Neural networks. | 
| org.apache.commons.math3.random | Random number and random data generators. | 
| org.apache.commons.math3.stat.inference | Classes providing hypothesis testing. | 
| Modifier and Type | Class and Description | 
|---|---|
| class  | AbstractRealDistributionBase class for probability distributions on the reals. | 
| class  | BetaDistributionImplements the Beta distribution. | 
| class  | CauchyDistributionImplementation of the Cauchy distribution. | 
| class  | ChiSquaredDistributionImplementation of the chi-squared distribution. | 
| class  | ConstantRealDistributionImplementation of the constant real distribution. | 
| class  | EnumeratedRealDistributionImplementation of a real-valued  EnumeratedDistribution. | 
| class  | ExponentialDistributionImplementation of the exponential distribution. | 
| class  | FDistributionImplementation of the F-distribution. | 
| class  | GammaDistributionImplementation of the Gamma distribution. | 
| class  | GumbelDistributionThis class implements the Gumbel distribution. | 
| class  | LaplaceDistributionThis class implements the Laplace distribution. | 
| class  | LevyDistributionThis class implements the 
 Lévy distribution. | 
| class  | LogisticDistributionThis class implements the Logistic distribution. | 
| class  | LogNormalDistributionImplementation of the log-normal (gaussian) distribution. | 
| class  | NakagamiDistributionThis class implements the Nakagami distribution. | 
| class  | NormalDistributionImplementation of the normal (gaussian) distribution. | 
| class  | ParetoDistributionImplementation of the Pareto distribution. | 
| class  | TDistributionImplementation of Student's t-distribution. | 
| class  | TriangularDistributionImplementation of the triangular real distribution. | 
| class  | UniformRealDistributionImplementation of the uniform real distribution. | 
| class  | WeibullDistributionImplementation of the Weibull distribution. | 
| Modifier and Type | Method and Description | 
|---|---|
| static FeatureInitializer | FeatureInitializerFactory. randomize(RealDistribution random,
         FeatureInitializer orig)Adds some amount of random data to the given initializer. | 
| Modifier and Type | Class and Description | 
|---|---|
| class  | EmpiricalDistributionRepresents 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. | 
| Modifier and Type | Method and Description | 
|---|---|
| protected RealDistribution | EmpiricalDistribution. getKernel(SummaryStatistics bStats)The within-bin smoothing kernel. | 
| Modifier and Type | Method and Description | 
|---|---|
| double | RandomDataImpl. nextInversionDeviate(RealDistribution distribution)Deprecated. 
 use the distribution's sample() method | 
| Modifier and Type | Method and Description | 
|---|---|
| static double | TestUtils. kolmogorovSmirnovStatistic(RealDistribution dist,
                          double[] data) | 
| double | KolmogorovSmirnovTest. 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 with  distribution, \(n\) is the
 length ofdataand \(F_n\) is the empirical distribution that puts mass \(1/n\) at
 each of the values indata. | 
| static double | TestUtils. kolmogorovSmirnovTest(RealDistribution dist,
                     double[] data) | 
| double | KolmogorovSmirnovTest. kolmogorovSmirnovTest(RealDistribution distribution,
                     double[] data)Computes the p-value, or observed significance level, of a one-sample  Kolmogorov-Smirnov test
 evaluating the null hypothesis that  dataconforms todistribution. | 
| static double | TestUtils. kolmogorovSmirnovTest(RealDistribution dist,
                     double[] data,
                     boolean strict) | 
| double | KolmogorovSmirnovTest. 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 that  dataconforms todistribution. | 
| static boolean | TestUtils. kolmogorovSmirnovTest(RealDistribution dist,
                     double[] data,
                     double alpha) | 
| boolean | KolmogorovSmirnovTest. kolmogorovSmirnovTest(RealDistribution distribution,
                     double[] data,
                     double alpha)Performs a  Kolmogorov-Smirnov
 test evaluating the null hypothesis that  dataconforms todistribution. | 
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