Package elki.math.statistics.distribution.estimator
Estimators for statistical distributions.
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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.