A library for dealing with probabilities, random variables, distributions, modelling and stochastic processes.
The library is written in F# and compiles with fable to Javascript for use in JS projects with all the nice guarantees and developer experiences that come with F#.
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- Publish package as a nuget package
- Github action to publish to nuget
- Github action to create npm branch and push to npm
- Add support for fitting to data (future)
Arcsine, Bernoulli, Beta, BetaBinomial, BetaPrime, Binomial, Biweight, Categorical, Cauchy, Chi, Chisq, Cosine, DiagNormal, DiagNormalCanon, Dirichlet, DiscreteUniform, DoubleExponential, EdgeworthMean, EdgeworthSum, EdgeworthZ, Erlang, Epanechnikov, Exponential, FDist, FisherNoncentralHypergeometric, Frechet, FullNormal, FullNormalCanon, Gamma, GeneralizedPareto, GeneralizedExtremeValue, Geometric, Gumbel, Hypergeometric, InverseWishart, InverseGamma, InverseGaussian, IsoNormal, IsoNormalCanon, Kolmogorov, KSDist, KSOneSided, Laplace, Levy, LKJ, LKJCholesky, Logistic, LogNormal, MatrixBeta, MatrixFDist, MatrixNormal, MatrixTDist, MixtureModel, Multinomial, MultivariateNormal, MvLogNormal, MvNormal, MvNormalCanon, MvNormalKnownCov, MvTDist, NegativeBinomial, NoncentralBeta, NoncentralChisq, NoncentralF, NoncentralHypergeometric, NoncentralT, Normal, NormalCanon, NormalInverseGaussian, Pareto, PGeneralizedGaussian, Poisson, PoissonBinomial, QQPair, Rayleigh, Rician, Skellam, Soliton, StudentizedRange, SymTriangularDist, TDist, TriangularDist, Triweight, Truncated, TruncatedNormal, Uniform, UnivariateGMM, VonMises, VonMisesFisher, WalleniusNoncentralHypergeometric, Weibull, Wishart, ZeroMeanIsoNormal, ZeroMeanIsoNormalCanon, ZeroMeanDiagNormal, ZeroMeanDiagNormalCanon, ZeroMeanFullNormal, ZeroMeanFullNormalCanon