# Inference tools for Markov Random Fields on lattices: The R package mrf2d

arXiv: https://arxiv.org/abs/2006.00383 · HTML: https://mlsanity.com/paper/2006.00383/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 May 2020.

## Built on by (most cited first, 2 of 2)

- [Sparse Interaction Neighborhood Selection for Markov Random Fields via Reversible Jump and Pseudoposteriors](https://mlsanity.com/paper/2204.05933/) (2022)
- [Convergence of Dirichlet Forms for MCMC Optimal Scaling with Dependent Target Distributions on Large Graphs](https://mlsanity.com/paper/2210.17042/) (2022)

## Abstract (arXiv)

Markov random fields on two-dimensional lattices are behind many image analysis methodologies. mrf2d provides tools for statistical inference on a class of discrete stationary Markov random field models with pairwise interaction, which includes many of the popular models such as the Potts model and texture image models. The package introduces representations of dependence structures and parameters, visualization functions and efficient (C++ based) implementations of sampling algorithms, common estimation methods and other key features of the model, providing a useful framework to implement algorithms and working with the model in general. This paper presents a description and details of the package, as well as some reproducible examples of usage.