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

Packages that use de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator

Package	Description
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.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.

Classes in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator used by de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise

Class and Description
DistributionEstimator Estimate distribution parameters from a sample.

Classes in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator used by de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator

Class and Description
AbstractExpMADEstimator Abstract base class for estimators based on the median and MAD.
AbstractLMMEstimator Abstract base class for L-Moments based estimators (LMM).
AbstractLogMADEstimator Abstract base class for estimators based on the median and MAD.
AbstractLogMeanVarianceEstimator Estimators that work on Mean and Variance only (i.e. the first two moments only).
AbstractLogMOMEstimator Abstract base class for estimators based on the statistical moments.
AbstractMADEstimator Abstract base class for estimators based on the median and MAD.
AbstractMeanVarianceEstimator Estimators that work on Mean and Variance only (i.e. the first two moments only).
AbstractMOMEstimator Abstract base class for estimators based on the statistical moments.
CauchyMADEstimator Estimate Cauchy distribution parameters using Median and MAD.
DistributionEstimator Estimate distribution parameters from a sample.
EMGOlivierNorbergEstimator Naive distribution estimation using mean and sample variance.
ExpMADDistributionEstimator Distribuition estimators that use the method of moments (MOM) in exponentiated data.
ExponentialLMMEstimator Estimate the parameters of a Gamma Distribution, using the methods of L-Moments (LMM).
ExponentialMADEstimator Estimate Exponential distribution parameters using Median and MAD.
ExponentialMedianEstimator Estimate Exponential distribution parameters using Median and MAD.
ExponentialMOMEstimator Estimate Exponential distribution parameters using the mean, which is the maximum-likelihood estimate (MLE), but not very robust.
GammaChoiWetteEstimator Estimate distribution parameters using the method by Choi and Wette.
GammaLMMEstimator Estimate the parameters of a Gamma Distribution, using the methods of L-Moments (LMM).
GammaMADEstimator Robust parameter estimation for the Gamma distribution.
GammaMOMEstimator Simple parameter estimation for the Gamma distribution.
GeneralizedExtremeValueLMMEstimator Estimate the parameters of a Generalized Extreme Value Distribution, using the methods of L-Moments (LMM).
GeneralizedLogisticAlternateLMMEstimator Estimate the parameters of a Generalized Logistic Distribution, using the methods of L-Moments (LMM).
GeneralizedParetoLMMEstimator Estimate the parameters of a Generalized Pareto Distribution (GPD), using the methods of L-Moments (LMM).
GumbelLMMEstimator Estimate the parameters of a Gumbel Distribution, using the methods of L-Moments (LMM).
GumbelMADEstimator Parameter estimation via median and median absolute deviation from median (MAD).
LaplaceLMMEstimator Estimate Laplace distribution parameters using the method of L-Moments (LMM).
LaplaceMADEstimator Estimate Laplace distribution parameters using Median and MAD.
LaplaceMLEEstimator Estimate Laplace distribution parameters using Median and mean deviation from median.
LMMDistributionEstimator Interface for distribution estimators based on the methods of L-Moments (LMM).
LogGammaAlternateExpMADEstimator Robust parameter estimation for the LogGamma distribution.
LogGammaChoiWetteEstimator Estimate distribution parameters using the method by Choi and Wette.
LogGammaLogMADEstimator Robust parameter estimation for the LogGamma distribution.
LogGammaLogMOMEstimator Simple parameter estimation for the Gamma distribution.
LogisticLMMEstimator Estimate the parameters of a Logistic Distribution, using the methods of L-Moments (LMM).
LogisticMADEstimator Estimate Logistic distribution parameters using Median and MAD.
LogLogisticMADEstimator Estimate Logistic distribution parameters using Median and MAD.
LogMADDistributionEstimator Distribuition estimators that use the method of moments (MOM) in logspace.
LogMOMDistributionEstimator 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.
LogNormalBilkovaLMMEstimator Alternate estimate the parameters of a log Gamma Distribution, using the methods of L-Moments (LMM) for the Generalized Normal Distribution.
LogNormalLevenbergMarquardtKDEEstimator Distribution parameter estimation using Levenberg-Marquardt iterative optimization and a kernel density estimation.
LogNormalLMMEstimator Estimate the parameters of a log Normal Distribution, using the methods of L-Moments (LMM) for the Generalized Normal Distribution.
LogNormalLogMADEstimator Estimator using Medians.
LogNormalLogMOMEstimator Naive distribution estimation using mean and sample variance.
MADDistributionEstimator Distribuition estimators that use the method of moments (MOM), i.e. that only need the statistical moments of a data set.
MeanVarianceDistributionEstimator Interface for estimators that only need mean and variance.
MOMDistributionEstimator Distribuition estimators that use the method of moments (MOM), i.e. that only need the statistical moments of a data set.
NormalLevenbergMarquardtKDEEstimator Distribution parameter estimation using Levenberg-Marquardt iterative optimization and a kernel density estimation.
NormalLMMEstimator Estimate the parameters of a normal distribution using the method of L-Moments (LMM).
NormalMADEstimator Estimator using Medians.
NormalMOMEstimator Naive maximum-likelihood estimations for the normal distribution using mean and sample variance.
RayleighLMMEstimator Estimate the scale parameter of a (non-shifted) RayleighDistribution using the method of L-Moments (LMM).
RayleighMADEstimator Estimate the parameters of a RayleighDistribution using the MAD.
RayleighMLEEstimator Estimate the scale parameter of a (non-shifted) RayleighDistribution using a maximum likelihood estimate.
SkewGNormalLMMEstimator Estimate the parameters of a skew Normal Distribution (Hoskin's Generalized Normal Distribution), using the methods of L-Moments (LMM).
UniformEnhancedMinMaxEstimator Slightly improved estimation, that takes sample size into account and enhances the interval appropriately.
UniformLMMEstimator Estimate the parameters of a normal distribution using the method of L-Moments (LMM).
UniformMADEstimator Estimate Uniform distribution parameters using Median and MAD.
UniformMinMaxEstimator Estimate the uniform distribution by computing min and max.
WaldMLEstimator Estimate parameter of the Wald distribution.
WaldMOMEstimator Estimate parameter of the Wald distribution.
WeibullLMMEstimator Estimate parameters of the Weibull distribution using the method of L-Moments (LMM).
WeibullLogMADEstimator Parameter estimation via median and median absolute deviation from median (MAD).
WeibullLogMOMEstimator Naive parameter estimation via least squares.

Classes in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator used by de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.meta

Class and Description
DistributionEstimator Estimate distribution parameters from a sample.
LMMDistributionEstimator Interface for distribution estimators based on the methods of L-Moments (LMM).
LogMADDistributionEstimator Distribuition estimators that use the method of moments (MOM) in logspace.
LogMOMDistributionEstimator 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.
MADDistributionEstimator Distribuition estimators that use the method of moments (MOM), i.e. that only need the statistical moments of a data set.
MOMDistributionEstimator Distribuition estimators that use the method of moments (MOM), i.e. that only need the statistical moments of a data set.