The dagger library for probabilistic programming in OCaml.
Currently implements:

• Single-site Metropolis-Hastings, a.k.a. lightweight Metropolis-Hastings

• Incrementalized single-site MH, similar to that implemented in Hakaru10

• Sequential Monte-Carlo, with systematic and stratified resampling

The main package is prbnmcn-dagger. Packages prbnmcn-dagger-gsl and prbnmcn-dagger-stats
provide distributions implemented respectively through the GSL (GPL-licensed) and
prbnmcn-stats (MIT-licensed).

Look no further for the documentation.

Examples will be made available in the examples subdirectory. For now, you'll find:

• an implementation of a 2d ising model and a toy study of its behaviour around its critical temperature

• an experiment on forecasting wind power production using an ad-hoc Kalman filter

Contributing

Contributions and issue reports are welcome. Development currently happen on https://gitlab.com/igarnier/monorepo/ but
I can take care of cherry-picking pull requests submitted here.

Trivia

The name dagger refers to two things:

• a good mathematical framework for giving a semantics to probabilistic
  programming is a certain dagger category of Markov
  kernels, see eg this or that paper;
  Bayesian inversion corresponds to a particular symmetry of a mathematical
  structure and this symmetry is denoted using the † symbol.

• the underlying representation of the probabilistic model when using the
  incrementalized backend is as a directed acyclic graph (ie a DAG, which
  sounds exactly like the French translation of dagger)