Bayesian Finite Mixtures of Ising Models
Methodology
2023-05-02 v1
Abstract
We introduce finite mixtures of Ising models as a novel approach to study multivariate patterns of associations of binary variables. Our proposed models combine the strengths of Ising models and multivariate Bernoulli mixture models. We examine conditions required for the identifiability of Ising mixture models, and develop a Bayesian framework for fitting them. Through simulation experiments and real data examples, we show that Ising mixture models lead to meaningful results for sparse binary contingency tables.
Keywords
Cite
@article{arxiv.2305.00588,
title = {Bayesian Finite Mixtures of Ising Models},
author = {Zhen Miao and Yen-Chi Chen and Adrian Dobra},
journal= {arXiv preprint arXiv:2305.00588},
year = {2023}
}