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pro vyhledávání: '"Walker, Stephen A."'
Autor:
Karabatsos, George, Walker, Stephen G.
We introduce a random partition model for Bayesian nonparametric regression. The model is based on infinitely-many disjoint regions of the range of a latent covariate-dependent Gaussian process. Given a realization of the process, the cluster of depe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3ad08d90994ff38ee43f60aa0cc2b71c
http://arxiv.org/abs/1212.3712
http://arxiv.org/abs/1212.3712
Autor:
Walker, Stephen G.
This note presents a simple and elegant sampler which could be used as an alternative to the reversible jump MCMC methodology.
Comment: Submitted to the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathem
Comment: Submitted to the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathem
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a93e4259a1b32cd2042f9fcfe43c41f7
http://arxiv.org/abs/0902.4117
http://arxiv.org/abs/0902.4117
In this paper, we provide an explicit probability distribution for classification purposes. It is derived from the Bayesian nonparametric mixture of Dirichlet process model, but with suitable modifications which remove unsuitable aspects of the class
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::57fc2c08352366259e605c0a5973f7e7
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