Some aspects of symmetric Gamma process mixtures
Statistics Theory
2016-07-29 v4 Methodology
Statistics Theory
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.
Keywords
Cite
@article{arxiv.1504.00476,
title = {Some aspects of symmetric Gamma process mixtures},
author = {Zacharie Naulet and Eric Barat},
journal= {arXiv preprint arXiv:1504.00476},
year = {2016}
}