383
v1v2v3v4 (latest)

Some aspects of symmetric Gamma process mixtures

Bayesian Analysis (BA), 2015
Abstract

In this article, we present some specific aspects of symmetric Gamma process mixtures for use in regression models. We propose a new Gibbs sampler for simulating the posterior and we establish adaptive posterior rates of convergence related to the Gaussian mean regression problem.

View on arXiv
Comments on this paper