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 Methods. pdf
• Backlund, Hobert, Jung and Khare (2020). A hybrid scan Gibbs sampler for Bayesian models with latent variables, Statistical Science. arXiv

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