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Quasi-optimal Bayesian procedures of many hypotheses testing

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  • K. J. Kachiashvili
  • M. A. Hashmi
  • A. Mueed

Abstract

Quasi-optimal procedures of testing many hypotheses are described in this paper. They significantly simplify the Bayesian algorithms of hypothesis testing and computation of the risk function. The relations allowing for obtaining the estimations for the values of average risks in optimum tasks are given. The obtained general solutions are reduced to concrete formulae for a multivariate normal distribution of probabilities. The methods of approximate computation of the risk functions in Bayesian tasks of testing many hypotheses are offered. The properties and interrelations of the developed methods and algorithms are investigated. On the basis of a simulation, the validity of the obtained results and conclusions drawn is presented.

Suggested Citation

  • K. J. Kachiashvili & M. A. Hashmi & A. Mueed, 2013. "Quasi-optimal Bayesian procedures of many hypotheses testing," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(1), pages 103-122, January.
    • Handle: RePEc:taf:japsta:v:40:y:2013:i:1:p:103-122
    DOI: 10.1080/02664763.2012.734797
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