Uses of Interface
de.lmu.ifi.dbs.elki.math.statistics.distribution.Distribution

Packages that use Distribution

Package	Description
de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering	Biclustering algorithms.
de.lmu.ifi.dbs.elki.data.synthetic.bymodel	Generator using a distribution model specified in an XML configuration file.
de.lmu.ifi.dbs.elki.datasource.filter.cleaning	Filters for data cleaning.
de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise	Normalizations operating on columns / variates; where each column is treated independently.
de.lmu.ifi.dbs.elki.math.statistics.distribution	Standard distributions, with random generation functionalities.
de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator	Estimators for statistical distributions.
de.lmu.ifi.dbs.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.
de.lmu.ifi.dbs.elki.utilities.scaling.outlier	Scaling of Outlier scores, that require a statistical analysis of the occurring values

Uses of Distribution in de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering declared as Distribution

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

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering with parameters of type Distribution

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

Constructors in de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering with parameters of type Distribution

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

Uses of Distribution in de.lmu.ifi.dbs.elki.data.synthetic.bymodel

Fields in de.lmu.ifi.dbs.elki.data.synthetic.bymodel with type parameters of type Distribution

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

Methods in de.lmu.ifi.dbs.elki.data.synthetic.bymodel that return Distribution

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

Methods in de.lmu.ifi.dbs.elki.data.synthetic.bymodel with parameters of type Distribution

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

Uses of Distribution in de.lmu.ifi.dbs.elki.datasource.filter.cleaning

Fields in de.lmu.ifi.dbs.elki.datasource.filter.cleaning declared as Distribution

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

Constructors in de.lmu.ifi.dbs.elki.datasource.filter.cleaning with parameters of type Distribution

Constructor and Description
ReplaceNaNWithRandomFilter(Distribution dist) Constructor.

Uses of Distribution in de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise

Fields in de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise with type parameters of type Distribution

Modifier and Type	Field and Description
private List<Distribution>	AttributeWiseCDFNormalization.dists Stores the estimated distributions
private List<Distribution>	AttributeWiseBetaNormalization.dists Stores the estimated distributions

Methods in de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise that return Distribution

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

Uses of Distribution in de.lmu.ifi.dbs.elki.math.statistics.distribution

Classes in de.lmu.ifi.dbs.elki.math.statistics.distribution that implement Distribution

Modifier and Type	Class and Description
class	AbstractDistribution Abstract base class for distributions.
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	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	KappaDistribution Kappa distribution, by Hosking.
class	LaplaceDistribution Laplace distribution also known as double exponential distribution
class	LogGammaAlternateDistribution Alternate Log-Gamma Distribution, with random generation and density functions.
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.
class	SkewGeneralizedNormalDistribution Generalized Gaussian distribution by adding a skew term, similar to lognormal distributions.
class	StudentsTDistribution Student's t distribution.
class	UniformDistribution Uniform distribution.
class	WaldDistribution Inverse Gaussian distribution aka Wald distribution
class	WeibullDistribution Weibull distribution.

Methods in de.lmu.ifi.dbs.elki.math.statistics.distribution that return Distribution

Modifier and Type	Method and Description
protected abstract Distribution	AbstractDistribution.Parameterizer.makeInstance()

Uses of Distribution in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator

Classes in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator with type parameters of type Distribution

Modifier and Type	Class and Description
class	AbstractExpMADEstimator<D extends Distribution> Abstract base class for estimators based on the median and MAD.
class	AbstractLMMEstimator<D extends Distribution> Abstract base class for L-Moments based estimators (LMM).
class	AbstractLogMADEstimator<D extends Distribution> Abstract base class for estimators based on the median and MAD.
class	AbstractLogMeanVarianceEstimator<D extends Distribution> Estimators that work on Mean and Variance only (i.e. the first two moments only).
class	AbstractLogMOMEstimator<D extends Distribution> Abstract base class for estimators based on the statistical moments.
class	AbstractMADEstimator<D extends Distribution> Abstract base class for estimators based on the median and MAD.
class	AbstractMeanVarianceEstimator<D extends Distribution> Estimators that work on Mean and Variance only (i.e. the first two moments only).
class	AbstractMOMEstimator<D extends Distribution> Abstract base class for estimators based on the statistical moments.
interface	DistributionEstimator<D extends Distribution> Estimate distribution parameters from a sample.
interface	ExpMADDistributionEstimator<D extends Distribution> Distribuition estimators that use the method of moments (MOM) in exponentiated data.
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	LogMOMDistributionEstimator<D extends Distribution> Distribuition 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> Distribuition estimators that use the method of moments (MOM), i.e. that only need the statistical moments of a data set.

Methods in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator that return Distribution

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

Uses of Distribution in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.meta

Classes in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.meta with type parameters of type Distribution

Modifier and Type	Class and Description
class	TrimmedEstimator<D extends Distribution> Trimmed wrapper around other estimators.
static class	TrimmedEstimator.Parameterizer<D extends Distribution> Parameterization class.
class	WinsorisingEstimator<D extends Distribution> Winsorising or Georgization estimator.
static class	WinsorisingEstimator.Parameterizer<D extends Distribution> Parameterization class.

Methods in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.meta that return Distribution

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

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

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

Methods in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.meta with parameters of type Distribution

Modifier and Type	Method and Description
private double	BestFitEstimator.testFit(double[] x, double[] test, Distribution dist) Test the quality of a fit.

Uses of Distribution in de.lmu.ifi.dbs.elki.utilities.scaling.outlier

Fields in de.lmu.ifi.dbs.elki.utilities.scaling.outlier declared as Distribution

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