  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.
