Bayesian likelihood robustness in linear models

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Bayesian likelihood robustness in linear models

TitleBayesian likelihood robustness in linear models
Publication TypeJournal Article
Year of Publication2009
AuthorsPena, D, Zamar, R, Yan, G
JournalJOURNAL OF STATISTICAL PLANNING AND INFERENCE
Volume139
Pagination2196-2207
Date PublishedJUL 1
Type of ArticleArticle
ISSN0378-3758
KeywordsBayesian inference, Heteroscedasticity, Kullback-Leibler divergence, Robust regression
AbstractThis paper deals with the problem of robustness of Bayesian regression with respect to the data. We first give a formal definition of Bayesian robustness to data contamination, prove that robustness according to the definition cannot be obtained by using heavy-tailed error distributions in linear regression models and propose a heteroscedastic approach to achieve the desired Bayesian robustness. (C) 2008 Elsevier B.V. All rights reserved.
DOI10.1016/j.jspi.2008.10.012