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.
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