On Bayes and Nash experimental designs for hypothesis testing problems

Singh, Satya Prakash and Davidov, Ori (2020) On Bayes and Nash experimental designs for hypothesis testing problems. Electronic Journal of Statistics, 14 (2). pp. 1-28. ISSN 1935-7524

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Abstract

In this communication we examine the relationship between maxi–min, Bayes and Nash designs for some hypothesis testing problems. In particular we consider the problem of sample allocation in the standard analysis of variance framework and show that the maxi–min design is also a Bayes solution with respect to the least favourable prior, as well as a solution to a game theoretic problem, which we refer to as a Nash design. In addition, an extension to tests for order is provided. © 2020, Institute of Mathematical Statistics. All rights reserved.

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IITH Creators:

IITH Creators	ORCiD

Item Type:

Article

Additional Information:

The research leading to this paper was conducted (mostly) while the first author was a postdoctoral fellow at the University of Haifa, Israel. The work of the second author is supported by the Israeli Science Foundation Grant No. 456/17 and gratefully acknowledged.

Uncontrolled Keywords:

ANOVA; Bayesian design; Maxi-min design; Nash equilibrium; Power

Subjects:

Mathematics
Mathematics > Numerical analysis

Divisions:

Department of Mathematics

Depositing User:

. LibTrainee 2021

Date Deposited:

16 Nov 2022 05:39

Last Modified:

16 Nov 2022 05:39