ON THE PROPERTIES OF SUBSET SELECTION PROCEDURES.

Abstract

Some desirable properties are studied of a selection procedure which selects the normal population with mean m and variance unity (i=1,2,...,k) if the observed sample mean x sub i from p contained in (x(Max)- d, x(max)). This rule earlier studied by Gupta (1956, 1965) is compared with the 'approximate' optimal rule D of Seal (1955). It is shown that the rule R is minimax. It is also shown that under the slippage configuration of means given by (m,m,...,m+ delta) the expected size of the selected subset using R is smaller than that corresponding to D and that the probability of a correct selection using R is strictly greater than that of D, provided delta satisfies some inequalities. Under a more general linear loss function, the Bayes rule for selecting a subset is also derived. (Author)

Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1965
Accession Number
AD0621151

Entities

People

  • John J. Deely
  • Shanti Gupta

Organizations

  • Purdue University

Tags

DTIC Thesaurus Topics

  • Inequalities
  • Probability

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms