'probably-baysig' contains definitions and functions for probabilistic and statistical inference.
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Math.Probably.Sampler defines the sampling function monad, as described by Sungwoo Park and implemented elsewhere (e.g. 'random-fu' and 'monte-carlo' packages)
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Math.Probably.PDF defines some common parametric log-probability density functions
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Math.Probably.FoldingStats defines statistics as folds that can be composed and calculated independently of the container of the underlying data.
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Strategy.* implements various transition operators for Markov Chain Monte Carlo, including Metropolis-Hastings, Hamiltonian Monte Carlo, NUTS, and continuous/discrete slice samplers.
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Math.Probably.MCMC implements functions and combinators for running Markov chains and interleaving transition operators.