See: Description
| Interface | Description |
|---|---|
| Distribution |
Statistical distributions, with their common functions.
|
| DistributionEstimator<D extends Distribution> |
Estimate distribution parameters from a sample.
|
| DistributionWithRandom |
Distribution that also has support for generating random numbers.
|
| Class | Description |
|---|---|
| BetaDistribution |
Beta Distribution with implementation of the regularized incomplete beta
function
|
| CauchyDistribution |
Cauchy distribution.
|
| ChiDistribution |
Chi distribution.
|
| ChiSquaredDistribution |
Chi-Squared distribution (a specialization of the Gamma distribution).
|
| ConstantDistribution |
Pseudo distribution, that has a unique constant value.
|
| ExponentialDistribution |
Exponential distribution.
|
| ExponentiallyModifiedGaussianDistribution |
Exponentially modified Gaussian (EMG) distribution (ExGaussian distribution)
is a combination of a normal distribution and an exponential distribution.
|
| ExponentiallyModifiedGaussianDistribution.OlivierNorbergEstimator |
Naive distribution estimation using mean and sample variance.
|
| ExponentiallyModifiedGaussianDistribution.OlivierNorbergEstimator.Parameterizer |
Parameterization class.
|
| GammaDistribution |
Gamma Distribution, with random generation and density functions.
|
| GammaDistribution.ChoiWetteEstimator |
Estimate distribution parameters using the method by Choi and Wette.
|
| GammaDistribution.ChoiWetteEstimator.Parameterizer |
Parameterization class.
|
| GammaDistribution.MADEstimator |
Robust parameter estimation for the Gamma distribution.
|
| GammaDistribution.MADEstimator.Parameterizer |
Parameterization class.
|
| GammaDistribution.NaiveEstimator |
Simple parameter estimation for the Gamma distribution.
|
| GammaDistribution.NaiveEstimator.Parameterizer |
Parameterization class.
|
| HaltonUniformDistribution |
Halton sequences are a pseudo-uniform distribution.
|
| LogGammaDistribution |
Gamma Distribution, with random generation and density functions.
|
| LogGammaDistribution.ChoiWetteEstimator |
Estimate distribution parameters using the method by Choi and Wette.
|
| LogGammaDistribution.ChoiWetteEstimator.Parameterizer |
Parameterization class.
|
| LogGammaDistribution.MADEstimator |
Robust parameter estimation for the LogGamma distribution.
|
| LogGammaDistribution.MADEstimator.Parameterizer |
Parameterization class.
|
| LogGammaDistribution.NaiveEstimator |
Simple parameter estimation for the Gamma distribution.
|
| LogGammaDistribution.NaiveEstimator.Parameterizer |
Parameterization class.
|
| LogNormalDistribution |
Log-Normal distribution.
|
| LogNormalDistribution.LevenbergMarquardtKDEEstimator |
Distribution parameter estimation using Levenberg-Marquardt iterative
optimization and a kernel density estimation.
|
| LogNormalDistribution.LevenbergMarquardtKDEEstimator.Parameterizer |
Parameterization class.
|
| LogNormalDistribution.MADEstimator |
Estimator using Medians.
|
| LogNormalDistribution.MADEstimator.Parameterizer |
Parameterization class.
|
| LogNormalDistribution.NaiveEstimator |
Naive distribution estimation using mean and sample variance.
|
| LogNormalDistribution.NaiveEstimator.Parameterizer |
Parameterization class.
|
| NormalDistribution |
Gaussian distribution aka normal distribution
|
| NormalDistribution.LevenbergMarquardtKDEEstimator |
Distribution parameter estimation using Levenberg-Marquardt iterative
optimization and a kernel density estimation.
|
| NormalDistribution.LevenbergMarquardtKDEEstimator.Parameterizer |
Parameterization class.
|
| NormalDistribution.MADEstimator |
Estimator using Medians.
|
| NormalDistribution.MADEstimator.Parameterizer |
Parameterization class.
|
| NormalDistribution.NaiveEstimator |
Naive distribution estimation using mean and sample variance.
|
| NormalDistribution.NaiveEstimator.Parameterizer |
Parameterization class.
|
| PoissonDistribution |
INCOMPLETE implementation of the poisson distribution.
|
| StudentsTDistribution |
Student's t distribution.
|
| UniformDistribution |
Uniform distribution.
|
| UniformDistribution.NaiveMinMaxEstimator |
Estimate the uniform distribution by computing min and max.
|
| UniformDistribution.NaiveMinMaxEstimator.Parameterizer |
Parameterization class.
|
| UniformDistribution.RefinedMinMaxEstimator |
Slightly improved estimation, that takes sample size into account.
|
| UniformDistribution.RefinedMinMaxEstimator.Parameterizer |
Parameterization class.
|
Standard distributions, with random generation functionalities.