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Abstract:
Bayesian statistical practice makes extensive use of versions of
objective Bayesian analysis. We discuss why this is so, and address
some of the criticisms that have been raised concerning objective
Bayesian analysis. The dangers of treating the issue too casually are
also considered. In particular, we suggest that the statistical
community should accept formal objective Bayesian techniques with
confidence, but should be more cautious about casual objective
Bayesian techniques.
Keywords: History of objective Bayes, reference priors,
matching priors, invariance, information, Jeffreys priors, frequentist
validation, subjective Bayes, elicitation, unification of statistics,
coherency, marginalization paradox, vague proper priors, data
dependent priors
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Abstract:
We address the position of subjectivism within Bayesian
statistics. we argue, firstly that the subjectivist Bayes approach is
the only feasible method for tacking many important practical
problems. Secondly, we describe the essential role of the subjectivist
approach in scientific analysis. Finally, we consider possible
modifications to the Bayesian approach form a subjectivist viewpoint.
Keywords: coherency, exchangeability, physical model analysis,
high reliability testing, objective Bayes, temporal sure preference
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