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PartialRejectionSampling.jl documentation

This module provides a Julia implementation of the Partial Rejection Sampling (PRS) methodology developed by Heng Guo , Mark Jerrum , Jingcheng Liu (2019). With PRS, you generate exact samples from product distributions subject to some constraints, see e.g., some Graph point processes and Spatial point processes.

Given an initial sample from the (unconstrained) product distribution:

  • Vanilla rejection sampling resample all variables if any constraint is violated; until all constraints are satisfied,
  • Partial rejection sampling instead identifies a subset of variables to be resampled, starting from variables involved in violated constraints, and preserves the state of the variables outside of this resampling set; until all constraints are satisfied.

In both cases, the output sample is guaranteed to have the right distribution, i.e., the product distribution subject to the prescribed constraints.

Getting Started

Installation

PartialRejectionSampling.jl is not yet a registered package. But you can to install it through

julia> ]add https://github.com/guilgautier/PartialRejectionSampling.jl

see also how to manage packages with Pkg.

Usage

To start using the package, simply enter

julia> using PartialRejectionSampling
# const PRS = PartialRejectionSampling is made available so you can then use
# PRS.<type/function_you_want_to_use>

Tutorial Jupyter notebooks

You can also have a look at the tutorial Jupyter notebooks to play with the code.

Index

Types

Functions