Tutorial on stochastic simulation in Haskell

Question

I'd like to use Haskell for stochastic simulation, but I don't know how. I've read Hutton's 'Programming in Haskell', and I'm comfortable writing deterministic functional programs. However, I don't know how to start writing stochastic simulations of the sort that are easy in imperative languages like R or python. Is there a tutorial or primer on this that I could read, or can anyone provide some tips on getting started?

Answer 1

There's a nice self-contained paper Erwig and Kollmansberger: Functional Pearls - Probabilistic Functional Programming in Haskell on this topic. I used this as a starting point for writing a natural language processor based on Hidden Markov Models in Haskell. There's a package that is based on this paper, which also seems to provide a basic interface to R plotting.

There's also an entry on the HaskellWiki with more links to hackage. In particular, the ProbabilityMonads package might be useful for you.