Bayesian Trend Filtering via Proximal Markov Chain Monte Carlo
Bayesian Trend Filtering via Proximal Markov Chain Monte Carlo
Proximal Markov chain Monte Carlo is a novel construct that lies at the intersection of Bayesian computation and convex optimization, which helped popularize the use of nondifferentiable priors in Bayesian statistics. Existing formulations of proximal MCMC, however, require hyperparameters and regularization parameters to be prespecified. In this article, we extend …