The Annals of Statistics

A Robust Bayesian Interpretation of Likelihood Regions

Larry Alan Wasserman

Full-text: Open access

Abstract

Likelihood regions are shown to be robust in the sense that their posterior probability content is relatively insensitive to contaminations of the prior. This provides a Bayesian interpretation of regions that are commonly used by frequentists to construct confidence intervals and whose use are also advocated by the pure likelihood approach.

Article information

Source
Ann. Statist. Volume 17, Number 3 (1989), 1387-1393.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
http://projecteuclid.org/euclid.aos/1176347277

Digital Object Identifier
doi:10.1214/aos/1176347277

Mathematical Reviews number (MathSciNet)
MR1015159

Zentralblatt MATH identifier
0681.62006

JSTOR
links.jstor.org

Subjects
Primary: 62A15
Secondary: 62F15: Bayesian inference

Keywords
Contaminated priors credible regions likelihood regions robust Bayesian inference

Citation

Wasserman, Larry Alan. A Robust Bayesian Interpretation of Likelihood Regions. Ann. Statist. 17 (1989), no. 3, 1387--1393. doi:10.1214/aos/1176347277. http://projecteuclid.org/euclid.aos/1176347277.


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