7 papers · 1 filter
A global spectral gap for Metropolis-adjusted Langevin algorithm with a uniformly randomized step size
Qian Qin
Let on , where is continuously differentiable and -strongly convex with a globally -Lipschitz gradient, $0<…
Solidarity of Spectral Gaps for Component-Wise Markov Chains
Youngwoo Kwon, Galin Jones, Qian Qin
Deterministic-scan and random-scan component-wise Markov chain Monte Carlo algorithms, such as Gibbs samplers and conditional Metropolis-Hastings, are popular approaches for sampli…
Convergence analysis of data augmentation algorithms in Bayesian lasso models with log-concave likelihoods
Jingkai Cui, Qian Qin
We study the convergence properties of a class of data augmentation algorithms targeting posterior distributions of Bayesian lasso models with log-concave likelihoods. Leveraging i…
Convergence Bounds for Monte Carlo Markov Chains
Qian Qin
This review paper, written for the second edition of the Handbook of Markov Chain Monte Carlo, provides an introduction to the study of convergence analysis for Markov chain Monte…
Geometric ergodicity of trans-dimensional Markov chain Monte Carlo algorithms
Qian Qin
This article studies the convergence properties of trans-dimensional MCMC algorithms when the total number of models is finite. It is shown that, for reversible and some non-revers…
Convergence Analysis of Data Augmentation Algorithms for Bayesian Robust Multivariate Linear Regression with Incomplete Data
Haoxiang Li, Qian Qin, Galin L. Jones
Gaussian mixtures are commonly used for modeling heavy-tailed error distributions in robust linear regression. Combining the likelihood of a multivariate robust linear regression m…