On bayes and nash experimental designs for hypothesis testing problems

Satya Prakash Singh, Ori Davidov

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)3976-4003
Number of pages28
JournalElectronic Journal of Statistics
Issue number2
StatePublished - 2020

Bibliographical note

Publisher Copyright:
© 2020, Institute of Mathematical Statistics. All rights reserved.


  • Bayesian design
  • Maxi-min design
  • Nash equilibrium
  • Power

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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