Article ID Journal Published Year Pages File Type
1149570 Journal of Statistical Planning and Inference 2009 12 Pages PDF
Abstract
This 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.
Related Topics
Physical Sciences and Engineering Mathematics Applied Mathematics
Authors
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