Foundations of neo-Bayesian statistics

• 成果类型: Article
• 署名作者: Amarante, Massimiliano
• 署名单位: Universite de Montreal; Universite de Montreal
• 刊物名称: JOURNAL OF ECONOMIC THEORY
• ISSN/ISSBN: 0022-0531
• DOI: 10.1016/j.jet.2009.04.001
• 发表日期: 2009
• 页码: 2146-2173
• 关键词: Neo-Bayesian statistics; Choquet integral; Invariant Bi-separable preferences; Affine functions; Extension comonotonic additive functionals

摘要

We study an axiomatic model of preferences, which contains as special cases Subjective Expected Utility, Choquet Expected Utility, Maxmin and Maxmax Expected Utility and many other models. First, we give a complete characterization of the class of functionals representing these preferences. Then, we show that any such functional can be represented as a Choquet integral I(f) = integral kappa(f)d nu where kappa : B(Sigma) -> A (C) is the canonical mapping from the space of bounded Sigma-measurable functions into the space of weak*-continuous affine functions on a weak*-compact, convex set C of probability measures on Sigma. Conversely, any preference relation defined by means of such functionals satisfies the axioms of the model we study. Different properties of the capacity give rise to different models. Our result shows that the idea of Choquet integration is general enough to embrace all the models mentioned above. In doing so, it widens the range of applicability of well-known procedures in robust statistics theory such as the Neyman-Pearson lemma for capacities [P.J. Huber, V. Strassen, Minimax tests and the Neyman-Pearson lemma for capacities, Ann. Statist. 1 (1973) 251-263], Bayes' theorem for capacities [J.B. Kadane, L. Wasserman, Bayes' theorem for Choquet capacities, Ann. Statist. 18 (1990) 1328-1339] or of results like the Law of Large numbers for capacities [F. Maccheroni, M. Marinacci, A strong law of large numbers for capacities, Ann. Probab. 33 (2005) 1171-1178]. (C) 2009 Elsevier Inc. All rights reserved.