Some Locally Optimal Subset Selection Rules.

Abstract

Let pi(o),pi(1),...,pi(k) be k = 1 independent populations where pi(i) has the associated density function f(x, theta sub i) with the unknown parameter belonging to an interval H of the real line. Two types of problems are studied: (1) to select from pi(1),...,pi(k) those populations, if any, that are better (to be suitably defined) than pi(o) which is the control population; and (2) to select from pi(1),...,pi(k) a subset preferably of small size so as to contain the best population. For both problems, some locally optimal selection rules are derived. The optimality criteria employed in the two problems are different. Further, the procedure for the second problem is based on ranks though the densities are assumed to be known but for the values of the parameters. The rule in the first case is applied to the special cases of (1) normal means comparison with common known variance and unequal sample sizes; (2) normal means comparison with common unknown variance and unequal sample sizes, and (3) gamma scale parameters comparison with unequal shape parameters. The rank procedure is specialized to the case of logistic distributions. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1981
Accession Number
ADA101923

Entities

People

  • Deng Yuang Huang
  • S. Panchapakesan

Organizations

  • Purdue University

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  • Human Systems

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Fields of Study

  • Mathematics

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  • Regression Analysis.
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