The Annals of Statistics

On Empirical Bayes Testing with Sequential Components

Rohana J. Karunamuni

Full-text: Open access

Abstract

We study the empirical Bayes decision theory with an $m$-truncated sequential statistical decision problem as the component. An empirical Bayes sequential decision procedure is constructed for the linear loss two-action problem. Asymptotic results are presented regarding the convergence of the Bayes risk of the empirical Bayes sequential decision procedure. With sequential components, an empirical Bayes sequential decision procedure selects both a stopping rule function and a terminal decision rule function for use in the component with parameter $\theta$.

Article information

Source
Ann. Statist., Volume 16, Number 3 (1988), 1270-1282.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176350961

Digital Object Identifier
doi:10.1214/aos/1176350961

Mathematical Reviews number (MathSciNet)
MR959202

Zentralblatt MATH identifier
0725.62011

JSTOR
links.jstor.org

Subjects
Primary: 62C12: Empirical decision procedures; empirical Bayes procedures
Secondary: 62H15: Hypothesis testing

Keywords
Empirical Bayes sequential decision procedures asymptotic optimality asymptotic superiority

Citation

Karunamuni, Rohana J. On Empirical Bayes Testing with Sequential Components. Ann. Statist. 16 (1988), no. 3, 1270--1282. doi:10.1214/aos/1176350961. https://projecteuclid.org/euclid.aos/1176350961


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