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Fast Markov chain Monte Carlo for high dimensional Bayesian regression models with shrinkage priors.
In the past decade, many Bayesian shrinkage models have been developed for linear regression problems where the number of covariates, $p$, is large. Computing the intractable posterior are often done… Expand
Central limit theorems for Markov chains based on their convergence rates in Wasserstein distance
Many tools are available to bound the convergence rate of Markov chains in total variation (TV) distance. Such results can be used to establish central limit theorems (CLT) that enable error… Expand