Research

Research Interests

  • Convergence rates of Markov chain Monte Carlo algorithms
  • Data augmentation algorithms
  • Bayesian regression models

Working Papers

  • Backlund, Jung, and Hobert (2020). Analysis of a Gibbs sampler for Bayesian linear regression with skewed and heavy-tailed errors.

Publications

  • Backlund and Hobert (2020). A note on the convergence rate of MCMC for robust Bayesian multivariate linear regression with proper priors, Computational and Mathematical Methodspdf
  • Backlund, Hobert, Jung and Khare (2020). A hybrid scan Gibbs sampler for Bayesian models with latent variables, Statistical SciencearXiv

MStat Project: An Overview of the Data Augmentation Algorithm
March 2017