Uses of Interface
org.hipparchus.distribution.RealDistribution

Packages that use RealDistribution

Package	Description
org.hipparchus.distribution.continuous	Implementations of common continuous distributions.
org.hipparchus.random	Random number and random data generators.
org.hipparchus.samples	Various examples.
org.hipparchus.stat.fitting	Statistical methods for fitting distributions.
org.hipparchus.stat.inference	Classes providing hypothesis testing.

Uses of RealDistribution in org.hipparchus.distribution.continuous

Classes in org.hipparchus.distribution.continuous that implement RealDistribution

Modifier and Type	Class and 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-valued EnumeratedDistribution.
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.hipparchus.random

Methods in org.hipparchus.random with parameters of type RealDistribution

Modifier and Type	Method and Description
double	RandomDataGenerator.nextDeviate(RealDistribution dist) Returns a random deviate from the given distribution.
double[]	RandomDataGenerator.nextDeviates(RealDistribution dist, int size) Returns an array of random deviates from the given distribution.

Uses of RealDistribution in org.hipparchus.samples

Methods in org.hipparchus.samples with parameters of type RealDistribution

Modifier and Type	Method and Description
static void	RealDistributionComparison.addCDFSeries(com.xeiam.xchart.Chart chart, RealDistribution distribution, String desc, int lowerBound, int upperBound)
static void	RealDistributionComparison.addPDFSeries(com.xeiam.xchart.Chart chart, RealDistribution distribution, String desc, int lowerBound, int upperBound)
static JComponent	RealDistributionComparison.createComponent(String distributionName, int minX, int maxX, String[] seriesText, RealDistribution... series)

Uses of RealDistribution in org.hipparchus.stat.fitting

Classes in org.hipparchus.stat.fitting that implement RealDistribution

Modifier and Type	Class and 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.hipparchus.stat.fitting that return RealDistribution

Modifier and Type	Method and Description
protected RealDistribution	EmpiricalDistribution.getKernel(StreamingStatistics bStats) The within-bin smoothing kernel.

Uses of RealDistribution in org.hipparchus.stat.inference

Methods in org.hipparchus.stat.inference with parameters of type RealDistribution

Modifier and Type	Method and Description
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 of data and \(F_n\) is the empirical distribution that puts mass \(1/n\) at each of the values in data.
static double	InferenceTestUtils.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 that data conforms to distribution.
static double	InferenceTestUtils.kolmogorovSmirnovTest(RealDistribution dist, double[] data)
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 data conforms to distribution.
static double	InferenceTestUtils.kolmogorovSmirnovTest(RealDistribution dist, double[] data, boolean strict)
boolean	KolmogorovSmirnovTest.kolmogorovSmirnovTest(RealDistribution distribution, double[] data, double alpha) Performs a Kolmogorov-Smirnov test evaluating the null hypothesis that data conforms to distribution.
static boolean	InferenceTestUtils.kolmogorovSmirnovTest(RealDistribution dist, double[] data, double alpha)