Abstract
MAP estimators and HPD credible sets are often criticized in the literature because of paradoxical behaviour due to a lack of invariance under reparametrization. In this paper, we propose a new version of MAP estimators and HPD credible sets that avoid this undesirable feature. Moreover, in the special case of non-informative prior, the new MAP estimators coincide with the invariant frequentist ML estimators. We also propose several adaptations in the case of nuisance parameters.
Citation
Pierre Druilhet. Jean-Michel Marin. "Invariant {HPD} credible sets and {MAP} estimators." Bayesian Anal. 2 (4) 681 - 691, December 2007. https://doi.org/10.1214/07-BA227
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