- Overview
- Package
- Class
- Use
- Tree
- Deprecated
- Index
See: Description
| Interface | Description |
|---|---|
| DistributionEstimator<D extends Distribution> |
Estimate distribution parameters from a sample.
|
| ExpMADDistributionEstimator<D extends Distribution> |
Distribuition estimators that use the method of moments (MOM) in
exponentiated data.
|
| LMMDistributionEstimator<D extends Distribution> |
Interface for distribution estimators based on the methods of L-Moments
(LMM).
|
| LogMADDistributionEstimator<D extends Distribution> |
Distribuition estimators that use the method of moments (MOM) in logspace.
|
| 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.
|
| 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.
|
| MeanVarianceDistributionEstimator<D extends Distribution> |
Interface for estimators that only need mean and variance.
|
| 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.
|
| Class | Description |
|---|---|
| AbstractExpMADEstimator<D extends Distribution> |
Abstract base class for estimators based on the median and MAD.
|
| AbstractLMMEstimator<D extends Distribution> |
Abstract base class for L-Moments based estimators (LMM).
|
| AbstractLogMADEstimator<D extends Distribution> |
Abstract base class for estimators based on the median and MAD.
|
| AbstractLogMeanVarianceEstimator<D extends Distribution> |
Estimators that work on Mean and Variance only (i.e. the first two moments
only).
|
| AbstractLogMOMEstimator<D extends Distribution> |
Abstract base class for estimators based on the statistical moments.
|
| AbstractMADEstimator<D extends Distribution> |
Abstract base class for estimators based on the median and MAD.
|
| AbstractMeanVarianceEstimator<D extends Distribution> |
Estimators that work on Mean and Variance only (i.e. the first two moments
only).
|
| AbstractMOMEstimator<D extends Distribution> |
Abstract base class for estimators based on the statistical moments.
|
| CauchyMADEstimator |
Estimate Cauchy distribution parameters using Median and MAD.
|
| CauchyMADEstimator.Parameterizer |
Parameterization class.
|
| EMGOlivierNorbergEstimator |
Naive distribution estimation using mean and sample variance.
|
| EMGOlivierNorbergEstimator.Parameterizer |
Parameterization class.
|
| ExponentialLMMEstimator |
Estimate the parameters of a Gamma Distribution, using the methods of
L-Moments (LMM).
|
| ExponentialLMMEstimator.Parameterizer |
Parameterization class.
|
| ExponentialMADEstimator |
Estimate Exponential distribution parameters using Median and MAD.
|
| ExponentialMADEstimator.Parameterizer |
Parameterization class.
|
| ExponentialMedianEstimator |
Estimate Exponential distribution parameters using Median and MAD.
|
| ExponentialMedianEstimator.Parameterizer |
Parameterization class.
|
| ExponentialMOMEstimator |
Estimate Exponential distribution parameters using the mean, which is the
maximum-likelihood estimate (MLE), but not very robust.
|
| ExponentialMOMEstimator.Parameterizer |
Parameterization class.
|
| GammaChoiWetteEstimator |
Estimate distribution parameters using the method by Choi and Wette.
|
| GammaChoiWetteEstimator.Parameterizer |
Parameterization class.
|
| GammaLMMEstimator |
Estimate the parameters of a Gamma Distribution, using the methods of
L-Moments (LMM).
|
| GammaLMMEstimator.Parameterizer |
Parameterization class.
|
| GammaMADEstimator |
Robust parameter estimation for the Gamma distribution.
|
| GammaMADEstimator.Parameterizer |
Parameterization class.
|
| GammaMOMEstimator |
Simple parameter estimation for the Gamma distribution.
|
| GammaMOMEstimator.Parameterizer |
Parameterization class.
|
| GeneralizedExtremeValueLMMEstimator |
Estimate the parameters of a Generalized Extreme Value Distribution, using
the methods of L-Moments (LMM).
|
| GeneralizedExtremeValueLMMEstimator.Parameterizer |
Parameterization class.
|
| GeneralizedLogisticAlternateLMMEstimator |
Estimate the parameters of a Generalized Logistic Distribution, using the
methods of L-Moments (LMM).
|
| GeneralizedLogisticAlternateLMMEstimator.Parameterizer |
Parameterization class.
|
| GeneralizedParetoLMMEstimator |
Estimate the parameters of a Generalized Pareto Distribution (GPD), using the
methods of L-Moments (LMM).
|
| GeneralizedParetoLMMEstimator.Parameterizer |
Parameterization class.
|
| GumbelLMMEstimator |
Estimate the parameters of a Gumbel Distribution, using the methods of
L-Moments (LMM).
|
| GumbelLMMEstimator.Parameterizer |
Parameterization class.
|
| GumbelMADEstimator |
Parameter estimation via median and median absolute deviation from median
(MAD).
|
| GumbelMADEstimator.Parameterizer |
Parameterization class.
|
| LaplaceLMMEstimator |
Estimate Laplace distribution parameters using the method of L-Moments (LMM).
|
| LaplaceLMMEstimator.Parameterizer |
Parameterization class.
|
| LaplaceMADEstimator |
Estimate Laplace distribution parameters using Median and MAD.
|
| LaplaceMADEstimator.Parameterizer |
Parameterization class.
|
| LaplaceMLEEstimator |
Estimate Laplace distribution parameters using Median and mean deviation from
median.
|
| LaplaceMLEEstimator.Parameterizer |
Parameterization class.
|
| LogGammaAlternateExpMADEstimator |
Robust parameter estimation for the LogGamma distribution.
|
| LogGammaAlternateExpMADEstimator.Parameterizer |
Parameterization class.
|
| LogGammaChoiWetteEstimator |
Estimate distribution parameters using the method by Choi and Wette.
|
| LogGammaChoiWetteEstimator.Parameterizer |
Parameterization class.
|
| LogGammaLogMADEstimator |
Robust parameter estimation for the LogGamma distribution.
|
| LogGammaLogMADEstimator.Parameterizer |
Parameterization class.
|
| LogGammaLogMOMEstimator |
Simple parameter estimation for the Gamma distribution.
|
| LogGammaLogMOMEstimator.Parameterizer |
Parameterization class.
|
| LogisticLMMEstimator |
Estimate the parameters of a Logistic Distribution, using the methods of
L-Moments (LMM).
|
| LogisticLMMEstimator.Parameterizer |
Parameterization class.
|
| LogisticMADEstimator |
Estimate Logistic distribution parameters using Median and MAD.
|
| LogisticMADEstimator.Parameterizer |
Parameterization class.
|
| LogLogisticMADEstimator |
Estimate Logistic distribution parameters using Median and MAD.
|
| LogLogisticMADEstimator.Parameterizer |
Parameterization class.
|
| LogNormalBilkovaLMMEstimator |
Alternate estimate the parameters of a log Gamma Distribution, using the
methods of L-Moments (LMM) for the Generalized Normal Distribution.
|
| LogNormalBilkovaLMMEstimator.Parameterizer |
Parameterization class.
|
| LogNormalLevenbergMarquardtKDEEstimator |
Distribution parameter estimation using Levenberg-Marquardt iterative
optimization and a kernel density estimation.
|
| LogNormalLevenbergMarquardtKDEEstimator.Parameterizer |
Parameterization class.
|
| LogNormalLMMEstimator |
Estimate the parameters of a log Normal Distribution, using the methods of
L-Moments (LMM) for the Generalized Normal Distribution.
|
| LogNormalLMMEstimator.Parameterizer |
Parameterization class.
|
| LogNormalLogMADEstimator |
Estimator using Medians.
|
| LogNormalLogMADEstimator.Parameterizer |
Parameterization class.
|
| LogNormalLogMOMEstimator |
Naive distribution estimation using mean and sample variance.
|
| LogNormalLogMOMEstimator.Parameterizer |
Parameterization class.
|
| NormalLevenbergMarquardtKDEEstimator |
Distribution parameter estimation using Levenberg-Marquardt iterative
optimization and a kernel density estimation.
|
| NormalLevenbergMarquardtKDEEstimator.Parameterizer |
Parameterization class.
|
| NormalLMMEstimator |
Estimate the parameters of a normal distribution using the method of
L-Moments (LMM).
|
| NormalLMMEstimator.Parameterizer |
Parameterization class.
|
| NormalMADEstimator |
Estimator using Medians.
|
| NormalMADEstimator.Parameterizer |
Parameterization class.
|
| NormalMOMEstimator |
Naive maximum-likelihood estimations for the normal distribution using mean
and sample variance.
|
| NormalMOMEstimator.Parameterizer |
Parameterization class.
|
| RayleighLMMEstimator |
Estimate the scale parameter of a (non-shifted) RayleighDistribution using
the method of L-Moments (LMM).
|
| RayleighLMMEstimator.Parameterizer |
Parameterization class.
|
| RayleighMADEstimator |
Estimate the parameters of a RayleighDistribution using the MAD.
|
| RayleighMADEstimator.Parameterizer |
Parameterization class.
|
| RayleighMLEEstimator |
Estimate the scale parameter of a (non-shifted) RayleighDistribution using a
maximum likelihood estimate.
|
| RayleighMLEEstimator.Parameterizer |
Parameterization class.
|
| SkewGNormalLMMEstimator |
Estimate the parameters of a skew Normal Distribution (Hoskin's Generalized
Normal Distribution), using the methods of L-Moments (LMM).
|
| SkewGNormalLMMEstimator.Parameterizer |
Parameterization class.
|
| UniformEnhancedMinMaxEstimator |
Slightly improved estimation, that takes sample size into account and
enhances the interval appropriately.
|
| UniformEnhancedMinMaxEstimator.Parameterizer |
Parameterization class.
|
| UniformLMMEstimator |
Estimate the parameters of a normal distribution using the method of
L-Moments (LMM).
|
| UniformLMMEstimator.Parameterizer |
Parameterization class.
|
| UniformMADEstimator |
Estimate Uniform distribution parameters using Median and MAD.
|
| UniformMADEstimator.Parameterizer |
Parameterization class.
|
| UniformMinMaxEstimator |
Estimate the uniform distribution by computing min and max.
|
| UniformMinMaxEstimator.Parameterizer |
Parameterization class.
|
| WaldMLEstimator |
Estimate parameter of the Wald distribution.
|
| WaldMLEstimator.Parameterizer |
Parameterization class.
|
| WaldMOMEstimator |
Estimate parameter of the Wald distribution.
|
| WaldMOMEstimator.Parameterizer |
Parameterization class.
|
| WeibullLMMEstimator |
Estimate parameters of the Weibull distribution using the method of L-Moments
(LMM).
|
| WeibullLMMEstimator.Parameterizer |
Parameterization class.
|
| WeibullLogMADEstimator |
Parameter estimation via median and median absolute deviation from median
(MAD).
|
| WeibullLogMADEstimator.Parameterizer |
Parameterization class.
|
| WeibullLogMOMEstimator |
Naive parameter estimation via least squares.
|
| WeibullLogMOMEstimator.Parameterizer |
Parameterization class.
|
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.