This package defines the necessary functions to enable automatic differentiation (AD) of the logpdf function from Distributions.jl using the packages Tracker.jl, Zygote.jl, ForwardDiff.jl and ReverseDiff.jl. The goal of this package is to make the output of logpdf differentiable wrt all continuous parameters of a distribution as well as the random variable in the case of continuous distributions.
AD of logpdf is fully supported and tested for the following distributions wrt all combinations of continuous variables (distribution parameters and/or the random variable) and using all defined distribution constructors:
- Univariate discrete
BernoulliBetaBinomialBinomialCategoricalGeometricNegativeBinomialPoissonPoissonBinomialSkellam
- Univariate continuous
ArcsineBetaBetaPrimeBiweightCauchyChiChisqCosineDistributions.AffineDistributionEpanechnikovErlangExponentialFDistFrechetGammaGeneralizedExtremeValueGeneralizedParetoGumbelInverseGammaInverseGaussianKolmogorovLaplaceLevyLogisticLogitNormalLogNormalNormalNormalCanonNormalInverseGaussianParetoPGeneralizedGaussianRayleighSemicircleSymTriangularDistTDistTriangularDistTriweightUniformWeibull
- Multivariate continuous
MvLogNormalMvNormal
- Matrix-variate continuous
MatrixBetaWishartInverseWishart
A number of distributions are still either broken or not fully supported for various reasons. See this issue. If you can fix any of the broken ones, a PR is welcome!