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Contains more than 40 statistical distributions, with support for most probability distribution measures and estimation methods.

Common interface for probability distributions.

Common interface for probability distributions.

Common interface for distributions which can be estimated from data.

Common interface for distributions which can be estimated from data.

Common interface for distributions which can be estimated from data.

Common interface for distributions which can be estimated from data.

Common interface for mixture distributions.

Common interface for multivariate probability distributions.

Common interface for multivariate probability distributions.

Common interface for sampleable distributions (i.e. distributions that allow the generation of new samples through the

method.

Common interface for univariate probability distributions.

Common interface for univariate probability distributions.

Common interface for distributions which can be estimated from data.

This namespace contains a huge collection of probability distributions, ranging the from the common and simple Normal (Gaussian) and Poisson distributions to Inverse-Wishart and multivariate mixture distributions, including many specialized univariate distributions used in statistical hypothesis testing. Some of those distributions include the MannWhitneyDistribution, TDistribution, WilcoxonDistribution, KolmogorovSmirnovDistribution and many others.

For a complete list of all univariate probability distributions, check the Accord.Statistics.Distributions.Univariate namespace. For a complete list of all multivariate distributions, please see the Accord.Statistics.Distributions.Multivariate namespace.

A list of density kernels such as the Gaussian kernel and the Epanechnikov kernel are available in the Accord.Statistics.Distributions.DensityKernels namespace.

The namespace class diagram is shown below.

The namespace class diagram for univariate distributions is shown below.

The namespace class diagram for multivariate distributions is shown below.

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