Convergence rate of a collapsed Gibbs sampler for crossed random effects models
Computation
2021-10-22 v2 Statistics Theory
Methodology
Statistics Theory
Abstract
In this paper, we analyze the convergence rate of a collapsed Gibbs sampler for crossed random effects models. Our results apply to a substantially larger range of models than previous works, including models that incorporate missingness mechanism and unbalanced level data. The theoretical tools involved in our analysis include a connection between relaxation time and autoregression matrix, concentration inequalities, and random matrix theory.
Keywords
Cite
@article{arxiv.2109.02849,
title = {Convergence rate of a collapsed Gibbs sampler for crossed random effects models},
author = {Swarnadip Ghosh and Chenyang Zhong},
journal= {arXiv preprint arXiv:2109.02849},
year = {2021}
}
Comments
42 pages, 12 figures