Uses of Interface
org.apache.commons.math3.distribution.RealDistribution
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Packages that use RealDistribution 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. -
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Uses of RealDistribution in org.apache.commons.math3.distribution
Classes in org.apache.commons.math3.distribution that implement RealDistribution Modifier and Type Class Description class
AbstractRealDistribution
Base class for probability distributions on the reals.class
BetaDistribution
Implements the Beta distribution.class
CauchyDistribution
Implementation of the Cauchy distribution.class
ChiSquaredDistribution
Implementation of the chi-squared distribution.class
ConstantRealDistribution
Implementation of the constant real distribution.class
EnumeratedRealDistribution
Implementation of a real-valuedEnumeratedDistribution
.class
ExponentialDistribution
Implementation of the exponential distribution.class
FDistribution
Implementation of the F-distribution.class
GammaDistribution
Implementation of the Gamma distribution.class
GumbelDistribution
This class implements the Gumbel distribution.class
LaplaceDistribution
This class implements the Laplace distribution.class
LevyDistribution
This class implements the Lévy distribution.class
LogisticDistribution
This class implements the Logistic distribution.class
LogNormalDistribution
Implementation of the log-normal (gaussian) distribution.class
NakagamiDistribution
This class implements the Nakagami distribution.class
NormalDistribution
Implementation of the normal (gaussian) distribution.class
ParetoDistribution
Implementation of the Pareto distribution.class
TDistribution
Implementation of Student's t-distribution.class
TriangularDistribution
Implementation of the triangular real distribution.class
UniformRealDistribution
Implementation of the uniform real distribution.class
WeibullDistribution
Implementation 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 RealDistribution Modifier and Type Method Description static FeatureInitializer
FeatureInitializerFactory. 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 RealDistribution Modifier and Type Class Description class
EmpiricalDistribution
Represents 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 RealDistribution Modifier and Type Method Description protected RealDistribution
EmpiricalDistribution. getKernel(SummaryStatistics bStats)
The within-bin smoothing kernel.private RealDistribution
EmpiricalDistribution. k(double x)
The within-bin kernel of the bin that x belongs to.Methods in org.apache.commons.math3.random with parameters of type RealDistribution Modifier and Type Method Description double
RandomDataImpl. 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 RealDistribution Modifier and Type Method Description private static void
KolmogorovSmirnovTest. jitter(double[] data, RealDistribution dist)
Adds random jitter todata
using deviates sampled fromdist
.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 withdistribution
, \(n\) is the length ofdata
and \(F_n\) is the empirical distribution that puts mass \(1/n\) at each of the values indata
.static double
TestUtils. kolmogorovSmirnovStatistic(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 thatdata
conforms todistribution
.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 thatdata
conforms todistribution
.boolean
KolmogorovSmirnovTest. kolmogorovSmirnovTest(RealDistribution distribution, double[] data, double alpha)
Performs a Kolmogorov-Smirnov test evaluating the null hypothesis thatdata
conforms todistribution
.static double
TestUtils. kolmogorovSmirnovTest(RealDistribution dist, double[] data)
static double
TestUtils. kolmogorovSmirnovTest(RealDistribution dist, double[] data, boolean strict)
static boolean
TestUtils. kolmogorovSmirnovTest(RealDistribution dist, double[] data, double alpha)
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