Pseudo-Marginal Slice Sampling

pmslice.py is a python module for running pseudo-marginal slice sampling It is documented in the module itself.

Pseudo-Marginal slice sampling takes a Markov chain Monte Carlo (MCMC) method that evaluates the log of an unnormalized probability function, and turns it into a method that only needs the log of an unbiased estimator of the function.

This small Python module makes it easy to drop pseudo-marginal slice sampling into whatever (Python) MCMC code you already have. In our demonstration demo.py a pseudo-marginal slice-sampling scheme only needs three extra lines of code compared to its conventional MCMC version. None of these lines required deriving anything problem-specific.

simple_slice.py is a helper used in the demonstration. The only file you need to drop into your MCMC codebase (and all that setup.py installs) is the module pmslice.py.

Please refer to the paper for more details, and links to other implementations.