Open Access
November 2019 Larry Brown’s Contributions to Parametric Inference, Decision Theory and Foundations: A Survey
James O. Berger, Anirban DasGupta
Statist. Sci. 34(4): 621-634 (November 2019). DOI: 10.1214/19-STS717

Abstract

This article gives a panoramic survey of the general area of parametric statistical inference, decision theory and foundations of statistics for the period 1965–2010 through the lens of Larry Brown’s contributions to varied aspects of this massive area. The article goes over sufficiency, shrinkage estimation, admissibility, minimaxity, complete class theorems, estimated confidence, conditional confidence procedures, Edgeworth and higher order asymptotic expansions, variational Bayes, Stein’s SURE, differential inequalities, geometrization of convergence rates, asymptotic equivalence, aspects of empirical process theory, inference after model selection, unified frequentist and Bayesian testing, and Wald’s sequential theory. A reasonably comprehensive bibliography is provided.

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James O. Berger. Anirban DasGupta. "Larry Brown’s Contributions to Parametric Inference, Decision Theory and Foundations: A Survey." Statist. Sci. 34 (4) 621 - 634, November 2019. https://doi.org/10.1214/19-STS717

Information

Published: November 2019
First available in Project Euclid: 8 January 2020

zbMATH: 07240219
MathSciNet: MR4048594
Digital Object Identifier: 10.1214/19-STS717

Keywords: Admissibility , ancillary , ‎asymptotic ‎equivalence , Bayes , conditional confidence , differential inequality , Edgeworth expansions , estimated confidence , minimax , sequential , shrinkage , sufficiency

Rights: Copyright © 2019 Institute of Mathematical Statistics

Vol.34 • No. 4 • November 2019
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