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March, 1990 Prior Envelopes Based on Belief Functions
Larry Alan Wasserman
Ann. Statist. 18(1): 454-464 (March, 1990). DOI: 10.1214/aos/1176347511

Abstract

We show that the mathematical structure of belief functions makes them suitable for generating classes of prior distributions to be used in robust Bayesian inference. In particular, the upper and lower bounds of the posterior probability content of a measurable subset of the parameter space may be calculated directly in terms of upper and lower expectations (Theorem 4.1). We also extend an integral representation given by Dempster to infinite sets (Theorem 2.1).

Citation

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Larry Alan Wasserman. "Prior Envelopes Based on Belief Functions." Ann. Statist. 18 (1) 454 - 464, March, 1990. https://doi.org/10.1214/aos/1176347511

Information

Published: March, 1990
First available in Project Euclid: 12 April 2007

zbMATH: 0711.62001
MathSciNet: MR1041404
Digital Object Identifier: 10.1214/aos/1176347511

Subjects:
Primary: 62A15
Secondary: 62F15

Keywords: Belief functions , Choquet capacities , Markov kernel , robust Bayesian inference

Rights: Copyright © 1990 Institute of Mathematical Statistics

Vol.18 • No. 1 • March, 1990
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