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A Java package that provides routines for various statistical distributions. Based on R version 2.14.1 (continuously updated; current as of R v3.3.0). The major difference is that JDistlib is thread safe. The library contains the density (pdf), cumulative (cdf), quantile, and random number generator (RNG) routines of the following distributions: Ansari, Beta, Binomial, Cauchy, Chi square, Exponential, Fisher's F, Gamma, Geometric, Hypergeometric, Kendall, Logistic, Log normal, Negative binomial, Noncentral beta, Noncentral chi square, Noncentral f, Noncentral t, Normal, Poisson, Sign Rank, Spearman, Student's T, Tukey, Uniform, Weibull, Wilcoxon, and many more. ...

Libagf is a machine learning library that includes adaptive kernel density estimators using Gaussian kernels and k-nearest neighbours. Operations include statistical classification, interpolation/non-linear regression and pdf estimation. For statistical classification there is a borders training feature for creating fast and general pre-trained models that nonetheless return the conditional probabilities. Libagf also includes clustering algorithms as well as comparison and validation routines. It is written in C++.

A suite of Matlab functions that calculate the tail probability / cdf / pdf / quantile of linear combination of random variables in one of the following classes: (1) symmetric random variables with support on the real axis (normal, Student's t, uniform and triangular); (2) random variables with support on the positive real axis (chi-squared and log-Lambert W x chi-squared distributions; inverse gamma distribution is temporarily disabled due to numerical issues).