Journal
STATISTICAL SCIENCE
Volume 19, Issue 1, Pages 58-80Publisher
INST MATHEMATICAL STATISTICS-IMS
DOI: 10.1214/088342304000000116
Keywords
admissibility; Bayesian model checking; conditional frequentist; confidence intervals; consistency; coverage; design; hierarchical models; nonparametric Bayes; objective Bayesian methods; p-values; reference priors; testing
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Statistics has struggled for nearly a century over the issue of whether the Bayesian or frequentist paradigm is superior. This debate is far from over and, indeed, should continue, since there are fundamental philosophical and pedagogical issues at stake. At the methodological level, however, the debate has become considerably muted, with the recognition that each approach has a great deal to contribute to statistical practice and each is actually essential for full development of the other approach. In this article, we embark upon a rather idiosyncratic walk through some of these issues.
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