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Nonparametric Bayesian models through probit stick-breaking processes

We describe a novel class of Bayesian nonparametric priors based on stick-breaking constructions where the weights of the process are constructed as probit transformations of normal random variables. We show that these priors are extremely flexible, allowing us to generate a great variety of models...

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Detalhes bibliográficos
Main Authors: Rodríguez, Abel, Dunson, David B.
Formato: Artigo
Idioma:Inglês
Publicado em: 2011
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC3865248/
https://ncbi.nlm.nih.gov/pubmed/24358072
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1214/11-BA605
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