On Bayesian robustness with the [var epsilon]-contamination class of priors

Agata Boratynska

Statistics & Probability Letters, 1996, vol. 26, issue 4, 323-328

Abstract: The problem of measuring the Bayesian robustness when prior distributions are [var epsilon]-contaminated is considered. The total variation metric in the space of the posterior distributions as a global measure of robustness is discussed. An upper bound for the measure when the prior distributions vary in an [var epsilon]-contamination class is given. Examples are presented.

Keywords: Bayesian; robustness; Classes; of; priors; Total; variation; metric (search for similar items in EconPapers)
Date: 1996
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