On Two-Stage Allocation Procedures for Selection Problems.

Abstract

This paper deals with the problem of deriving two-stage allocation procedures for selecting the best normal population. If the prior distribution is assumed to be known, an exact Bayes two-stage allocation procedure is obtained. If the prior distribution depends on some unknown parameter, an adaptive two-stage allocation procedure is proposed. Using the empirical Bayes formulation, we prove that the proposed adaptive two-stage allocation procedure has some asymptotic optimallity property.

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Document Details

Document Type
Technical Report
Publication Date
Dec 08, 1987
Accession Number
ADA190766

Entities

People

  • Shanti Gupta
  • Tachen Liang

Organizations

  • Purdue University

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Availability
  • Bayesian Networks
  • Classification
  • Intervals
  • Military Research
  • Models
  • New York
  • Normal Distribution
  • Observation
  • Probability
  • Procurement
  • Security
  • Sequences
  • Statistics
  • United States
  • United States Government
  • Universities

Fields of Study

  • Mathematics

Readers

  • Statistical inference.