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February 1999 Integrated likelihood methods for eliminating nuisance parameters
James O. Berger, Brunero Liseo, Robert L. Wolpert
Statist. Sci. 14(1): 1-28 (February 1999). DOI: 10.1214/ss/1009211804

Abstract

Elimination of nuisance parameters is a central problem in statistical inference and has been formally studied in virtually all approaches to inference. Perhaps the least studied approach is elimination of nuisance parameters through integration, in the sense that this is viewed as an almost incidental byproduct of Bayesian analysis and is hence not something which is deemed to require separate study. There is, however, considerable value in considering integrated likelihood on its own, especially versions arising from default or noninformative priors. In this paper, we review such common integrated likelihoods and discuss their strengths and weaknesses relative to other methods.

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James O. Berger. Brunero Liseo. Robert L. Wolpert. "Integrated likelihood methods for eliminating nuisance parameters." Statist. Sci. 14 (1) 1 - 28, February 1999. https://doi.org/10.1214/ss/1009211804

Information

Published: February 1999
First available in Project Euclid: 24 December 2001

zbMATH: 1059.62521
MathSciNet: MR1702200
Digital Object Identifier: 10.1214/ss/1009211804

Rights: Copyright © 1999 Institute of Mathematical Statistics

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Vol.14 • No. 1 • February 1999
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