Some Locally Optimal Subset Selection Rules for Comparison with a Control.

Abstract

The goal is to select from pi sub 1,..., pi sub k (experimental treatments) those populations, if any, that are better (suitably defined) than pi sub 0 which is the control population. A locally optimal rule is derived in the class of rules for which Pr(pi sub i is selected) = gamma sub i, 1 = 1,...,k, when theta sub 0 = theta sub 1 =...= theta sub k. The criterion used for local optimality amounts to maximizing the efficiency in a certain sense of the rule in picking out the superior populations for specific configurations of theta = (theta sub 0,...,theta sub k) in a neighborhood of an equiparameter configuration. The general result is then applied to the following special cases: (a) normal means comparison - common known variance, (b) normal means comparison - common unknown variance, (c) gamma scale parameters comparison - known (unequal) shape parameters, and (d) comparison of regression slopes. In all these cases, the rule is obtained based on samples of unequal sizes.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1982
Accession Number
ADA120938

Entities

People

  • Deng Yuang Huang
  • S. Panchapakesan
  • Sheng-tsaing Tseng

Organizations

  • Purdue University

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  • Analytical Mechanics
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