83 citations · 316 across the 25 of their papers we have counts for
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math.ST2017
Convergence complexity analysis of Albert and Chib's algorithm for Bayesian probit regression
Qian Qin, James P. Hobert
The use of MCMC algorithms in high dimensional Bayesian problems has become routine. This has spurred so-called convergence complexity analysis, the goal of which is to ascertain h…
math.ST2017
Fast Monte Carlo Markov chains for Bayesian shrinkage models with random effects
Tavis Abrahamsen, James P. Hobert
When performing Bayesian data analysis using a general linear mixed model, the resulting posterior density is almost always analytically intractable. However, if proper conditional…
math.ST2017★ 3 cited
Estimating the spectral gap of a trace-class Markov operator
Qian Qin, James P. Hobert, Kshitij Khare
The utility of a Markov chain Monte Carlo algorithm is, in large part, determined by the size of the spectral gap of the corresponding Markov operator. However, calculating (and ev…