Uses of Interface
elki.math.statistics.distribution.Distribution

Packages that use Distribution

Package	Description
elki.clustering.biclustering	Biclustering algorithms.
elki.data.synthetic.bymodel	Generator using a distribution model specified in an XML configuration file.
elki.datasource.filter.cleaning	Filters for data cleaning.
elki.datasource.filter.normalization.columnwise	Normalizations operating on columns / variates; where each column is treated independently.
elki.datasource.filter.transform	Data space transformations.
elki.math.statistics.distribution	Standard distributions, with random generation functionalities.
elki.math.statistics.distribution.estimator	Estimators for statistical distributions.
elki.math.statistics.distribution.estimator.meta	Meta estimators: estimators that do not actually estimate themselves, but instead use other estimators, e.g., on a trimmed data set, or as an ensemble.
elki.utilities.scaling.outlier	Scaling of outlier scores, that require a statistical analysis of the occurring values.

Uses of Distribution in elki.clustering.biclustering

Fields in elki.clustering.biclustering declared as Distribution

Modifier and Type	Field	Description
private Distribution	ChengAndChurch.dist	Distribution to sample random replacement values from.
private Distribution	ChengAndChurch.Par.dist	Distribution of replacement values.

Methods in elki.clustering.biclustering with parameters of type Distribution

Modifier and Type	Method	Description
protected void	ChengAndChurch.BiclusterCandidate.maskMatrix(double[][] mat, Distribution replacement, java.util.Random rnd)	Updates the mask with replacement values for all data in the given rows and columns.

Constructors in elki.clustering.biclustering with parameters of type Distribution

Constructor	Description
ChengAndChurch(double delta, double alpha, int n, Distribution dist, RandomFactory rnd)	Constructor.

Uses of Distribution in elki.data.synthetic.bymodel

Fields in elki.data.synthetic.bymodel with type parameters of type Distribution

Modifier and Type	Field	Description
private java.util.List<Distribution>	GeneratorSingleCluster.axes	The distribution generators for each axis

Methods in elki.data.synthetic.bymodel that return Distribution

Modifier and Type	Method	Description
Distribution	GeneratorSingleCluster.getDistribution(int i)	Get distribution along (generator) axis i.

Methods in elki.data.synthetic.bymodel with parameters of type Distribution

Modifier and Type	Method	Description
void	GeneratorSingleCluster.addGenerator(Distribution gen, java.util.Random rnd)	Add a new generator to the cluster.

Uses of Distribution in elki.datasource.filter.cleaning

Fields in elki.datasource.filter.cleaning declared as Distribution

Modifier and Type	Field	Description
private Distribution	ReplaceNaNWithRandomFilter.dist	Distribution to generate replacement values with.
private Distribution	ReplaceNaNWithRandomFilter.Par.dist	Distribution to generate replacement values with.

Constructors in elki.datasource.filter.cleaning with parameters of type Distribution

Constructor	Description
ReplaceNaNWithRandomFilter(Distribution dist, RandomFactory rnd)	Constructor.

Uses of Distribution in elki.datasource.filter.normalization.columnwise

Fields in elki.datasource.filter.normalization.columnwise with type parameters of type Distribution

Modifier and Type	Field	Description
protected java.util.List<Distribution>	AttributeWiseCDFNormalization.dists	Stores the estimated distributions

Methods in elki.datasource.filter.normalization.columnwise that return Distribution

Modifier and Type	Method	Description
protected Distribution	AttributeWiseCDFNormalization.findBestFit(java.util.List<V> col, AttributeWiseCDFNormalization.Adapter adapter, int d, double[] test)	Find the best fitting distribution.

Uses of Distribution in elki.datasource.filter.transform

Fields in elki.datasource.filter.transform declared as Distribution

Modifier and Type	Field	Description
(package private) Distribution	HistogramJitterFilter.dist	Random generator.

Uses of Distribution in elki.math.statistics.distribution

Classes in elki.math.statistics.distribution that implement Distribution

Modifier and Type	Class	Description
class	BetaDistribution	Beta Distribution with implementation of the regularized incomplete beta function
class	CauchyDistribution	Cauchy distribution.
class	ChiDistribution	Chi distribution.
class	ChiSquaredDistribution	Chi-Squared distribution (a specialization of the Gamma distribution).
class	ConstantDistribution	Pseudo distribution, that has a unique constant value.
class	ExpGammaDistribution	Exp-Gamma Distribution, with random generation and density functions.
class	ExponentialDistribution	Exponential distribution.
class	ExponentiallyModifiedGaussianDistribution	Exponentially modified Gaussian (EMG) distribution (ExGaussian distribution) is a combination of a normal distribution and an exponential distribution.
class	GammaDistribution	Gamma Distribution, with random generation and density functions.
class	GeneralizedExtremeValueDistribution	Generalized Extreme Value (GEV) distribution, also known as Fisher–Tippett distribution.
class	GeneralizedLogisticAlternateDistribution	Generalized logistic distribution.
class	GeneralizedLogisticDistribution	Generalized logistic distribution.
class	GeneralizedParetoDistribution	Generalized Pareto Distribution (GPD), popular for modeling long tail distributions.
class	GumbelDistribution	Gumbel distribution, also known as Log-Weibull distribution.
class	HaltonUniformDistribution	Halton sequences are a pseudo-uniform distribution.
class	InverseGaussianDistribution	Inverse Gaussian distribution aka Wald distribution.
class	KappaDistribution	Kappa distribution, by Hosking.
class	LaplaceDistribution	Laplace distribution also known as double exponential distribution
class	LogGammaDistribution	Log-Gamma Distribution, with random generation and density functions.
class	LogisticDistribution	Logistic distribution.
class	LogLogisticDistribution	Log-Logistic distribution also known as Fisk distribution.
class	LogNormalDistribution	Log-Normal distribution.
class	NormalDistribution	Gaussian distribution aka normal distribution
class	PoissonDistribution	INCOMPLETE implementation of the poisson distribution.
class	RayleighDistribution	Rayleigh distribution, a special case of the Weibull distribution.
class	SkewGeneralizedNormalDistribution	Generalized normal distribution by adding a skew term, similar to lognormal distributions.
class	StudentsTDistribution	Student's t distribution.
class	UniformDistribution	Uniform distribution.
class	WeibullDistribution	Weibull distribution.

Uses of Distribution in elki.math.statistics.distribution.estimator

Classes in elki.math.statistics.distribution.estimator with type parameters of type Distribution

Modifier and Type	Interface	Description
interface	DistributionEstimator<D extends Distribution>	Estimate distribution parameters from a sample.
interface	LMMDistributionEstimator<D extends Distribution>	Interface for distribution estimators based on the methods of L-Moments (LMM).
interface	LogMADDistributionEstimator<D extends Distribution>	Distribuition estimators that use the method of moments (MOM) in logspace.
interface	LogMeanVarianceEstimator<D extends Distribution>	Estimators that work on Mean and Variance only (i.e. the first two moments only).
interface	LogMOMDistributionEstimator<D extends Distribution>	Distribution estimators that use the method of moments (MOM) in logspace, i.e. that only need the statistical moments of a data set after logarithms.
interface	MADDistributionEstimator<D extends Distribution>	Distribuition estimators that use the method of moments (MOM), i.e. that only need the statistical moments of a data set.
interface	MeanVarianceDistributionEstimator<D extends Distribution>	Interface for estimators that only need mean and variance.
interface	MOMDistributionEstimator<D extends Distribution>	Distribution estimators that use the method of moments (MOM), i.e. that only need the statistical moments of a data set.

Methods in elki.math.statistics.distribution.estimator that return Distribution

Modifier and Type	Method	Description
Distribution	UniformMinMaxEstimator.estimate(double min, double max)	Estimate parameters from minimum and maximum observed.

Uses of Distribution in elki.math.statistics.distribution.estimator.meta

Classes in elki.math.statistics.distribution.estimator.meta with type parameters of type Distribution

Modifier and Type	Class	Description
class	TrimmedEstimator<D extends Distribution>	Trimmed wrapper around other estimators.
static class	TrimmedEstimator.Par<D extends Distribution>	Parameterization class.
class	WinsorizingEstimator<D extends Distribution>	Winsorizing or Georgization estimator.
static class	WinsorizingEstimator.Par<D extends Distribution>	Parameterization class.

Fields in elki.math.statistics.distribution.estimator.meta declared as Distribution

Modifier and Type	Field	Description
(package private) Distribution	BestFitEstimator.BestFit.dist	Best match.

Methods in elki.math.statistics.distribution.estimator.meta that return Distribution

Modifier and Type	Method	Description
<A> Distribution	BestFitEstimator.estimate(A data, NumberArrayAdapter<?,A> adapter)

Methods in elki.math.statistics.distribution.estimator.meta that return types with arguments of type Distribution

Modifier and Type	Method	Description
java.lang.Class<? super Distribution>	BestFitEstimator.getDistributionClass()

Methods in elki.math.statistics.distribution.estimator.meta with parameters of type Distribution

Modifier and Type	Method	Description
void	BestFitEstimator.BestFit.test(DistributionEstimator<?> est, Distribution d)	Test the goodness of fit, keep the best.
private static double	BestFitEstimator.BestFit.testFit(double[] x, double[] test, Distribution dist)	Test the quality of a fit.

Uses of Distribution in elki.utilities.scaling.outlier

Fields in elki.utilities.scaling.outlier declared as Distribution

Modifier and Type	Field	Description
private Distribution	COPOutlierScaling.dist	Score distribution.