Package elki.math.statistics.distribution.estimator

Estimators for statistical distributions.

Interface Summary

Interface	Description
DistributionEstimator<D extends Distribution>	Estimate distribution parameters from a sample.
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.
LogMeanVarianceEstimator<D extends Distribution>	Estimators that work on Mean and Variance only (i.e. the first two moments only).
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.
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>	Distribution estimators that use the method of moments (MOM), i.e. that only need the statistical moments of a data set.

Class Summary

Class	Description
CauchyMADEstimator	Estimate Cauchy distribution parameters using Median and MAD.
CauchyMADEstimator.Par	Parameterization class.
EMGOlivierNorbergEstimator	Naive distribution estimation using mean and sample variance.
EMGOlivierNorbergEstimator.Par	Parameterization class.
ExpGammaExpMOMEstimator	Simple parameter estimation for the ExpGamma distribution.
ExpGammaExpMOMEstimator.Par	Parameterization class.
ExponentialLMMEstimator	Estimate the parameters of a Gamma Distribution, using the methods of L-Moments (LMM).
ExponentialLMMEstimator.Par	Parameterization class.
ExponentialMADEstimator	Estimate Exponential distribution parameters using Median and MAD.
ExponentialMADEstimator.Par	Parameterization class.
ExponentialMedianEstimator	Estimate Exponential distribution parameters using Median and MAD.
ExponentialMedianEstimator.Par	Parameterization class.
ExponentialMOMEstimator	Estimate Exponential distribution parameters using the mean, which is the maximum-likelihood estimate (MLE), but not very robust.
ExponentialMOMEstimator.Par	Parameterization class.
GammaChoiWetteEstimator	Estimate distribution parameters using the method by Choi and Wette.
GammaChoiWetteEstimator.Par	Parameterization class.
GammaLMMEstimator	Estimate the parameters of a Gamma Distribution, using the methods of L-Moments (LMM).
GammaLMMEstimator.Par	Parameterization class.
GammaMOMEstimator	Simple parameter estimation for the Gamma distribution.
GammaMOMEstimator.Par	Parameterization class.
GeneralizedExtremeValueLMMEstimator	Estimate the parameters of a Generalized Extreme Value Distribution, using the methods of L-Moments (LMM).
GeneralizedExtremeValueLMMEstimator.Par	Parameterization class.
GeneralizedLogisticAlternateLMMEstimator	Estimate the parameters of a Generalized Logistic Distribution, using the methods of L-Moments (LMM).
GeneralizedLogisticAlternateLMMEstimator.Par	Parameterization class.
GeneralizedParetoLMMEstimator	Estimate the parameters of a Generalized Pareto Distribution (GPD), using the methods of L-Moments (LMM).
GeneralizedParetoLMMEstimator.Par	Parameterization class.
GumbelLMMEstimator	Estimate the parameters of a Gumbel Distribution, using the methods of L-Moments (LMM).
GumbelLMMEstimator.Par	Parameterization class.
GumbelMADEstimator	Parameter estimation via median and median absolute deviation from median (MAD).
GumbelMADEstimator.Par	Parameterization class.
InverseGaussianMLEstimator	Estimate parameter of the inverse Gaussian (Wald) distribution.
InverseGaussianMLEstimator.Par	Parameterization class.
InverseGaussianMOMEstimator	Estimate parameter of the inverse Gaussian (Wald) distribution.
InverseGaussianMOMEstimator.Par	Parameterization class.
LaplaceLMMEstimator	Estimate Laplace distribution parameters using the method of L-Moments (LMM).
LaplaceLMMEstimator.Par	Parameterization class.
LaplaceMADEstimator	Estimate Laplace distribution parameters using Median and MAD.
LaplaceMADEstimator.Par	Parameterization class.
LaplaceMLEEstimator	Estimate Laplace distribution parameters using Median and mean deviation from median.
LaplaceMLEEstimator.Par	Parameterization class.
LogGammaLogMOMEstimator	Simple parameter estimation for the LogGamma distribution.
LogGammaLogMOMEstimator.Par	Parameterization class.
LogisticLMMEstimator	Estimate the parameters of a Logistic Distribution, using the methods of L-Moments (LMM).
LogisticLMMEstimator.Par	Parameterization class.
LogisticMADEstimator	Estimate Logistic distribution parameters using Median and MAD.
LogisticMADEstimator.Par	Parameterization class.
LogLogisticMADEstimator	Estimate Logistic distribution parameters using Median and MAD.
LogLogisticMADEstimator.Par	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.Par	Parameterization class.
LogNormalLevenbergMarquardtKDEEstimator	Distribution parameter estimation using Levenberg-Marquardt iterative optimization and a kernel density estimation.
LogNormalLevenbergMarquardtKDEEstimator.Par	Parameterization class.
LogNormalLMMEstimator	Estimate the parameters of a log Normal Distribution, using the methods of L-Moments (LMM) for the Generalized Normal Distribution.
LogNormalLMMEstimator.Par	Parameterization class.
LogNormalLogMADEstimator	Estimator using Medians.
LogNormalLogMADEstimator.Par	Parameterization class.
LogNormalLogMOMEstimator	Naive distribution estimation using mean and sample variance.
LogNormalLogMOMEstimator.Par	Parameterization class.
NormalLevenbergMarquardtKDEEstimator	Distribution parameter estimation using Levenberg-Marquardt iterative optimization and a kernel density estimation.
NormalLevenbergMarquardtKDEEstimator.Par	Parameterization class.
NormalLMMEstimator	Estimate the parameters of a normal distribution using the method of L-Moments (LMM).
NormalLMMEstimator.Par	Parameterization class.
NormalMADEstimator	Estimator using Medians.
NormalMADEstimator.Par	Parameterization class.
NormalMOMEstimator	Naive maximum-likelihood estimations for the normal distribution using mean and sample variance.
NormalMOMEstimator.Par	Parameterization class.
RayleighLMMEstimator	Estimate the scale parameter of a (non-shifted) RayleighDistribution using the method of L-Moments (LMM).
RayleighLMMEstimator.Par	Parameterization class.
RayleighMADEstimator	Estimate the parameters of a RayleighDistribution using the MAD.
RayleighMADEstimator.Par	Parameterization class.
RayleighMLEEstimator	Estimate the scale parameter of a (non-shifted) RayleighDistribution using a maximum likelihood estimate.
RayleighMLEEstimator.Par	Parameterization class.
SkewGNormalLMMEstimator	Estimate the parameters of a skew Normal Distribution (Hoskin's Generalized Normal Distribution), using the methods of L-Moments (LMM).
SkewGNormalLMMEstimator.Par	Parameterization class.
UniformEnhancedMinMaxEstimator	Slightly improved estimation, that takes sample size into account and enhances the interval appropriately.
UniformEnhancedMinMaxEstimator.Par	Parameterization class.
UniformLMMEstimator	Estimate the parameters of a normal distribution using the method of L-Moments (LMM).
UniformLMMEstimator.Par	Parameterization class.
UniformMADEstimator	Estimate Uniform distribution parameters using Median and MAD.
UniformMADEstimator.Par	Parameterization class.
UniformMinMaxEstimator	Estimate the uniform distribution by computing min and max.
UniformMinMaxEstimator.Par	Parameterization class.
WeibullLMMEstimator	Estimate parameters of the Weibull distribution using the method of L-Moments (LMM).
WeibullLMMEstimator.Par	Parameterization class.
WeibullLogMADEstimator	Parameter estimation via median and median absolute deviation from median (MAD).
WeibullLogMADEstimator.Par	Parameterization class.