Selection Procedures for A Problem in Analysis of Variance.

Abstract

There are many situations in the analysis of variance where an experimenter would like to make comparisons among (and select the 'best' set) the treatments. In this paper we study the problem where the data are based on a completely randomized block design. It is shown that the subset selection approach is a useful method to make appropriate 'identification' among the hypotheses and the selected subset. We propose an optimal selection procedure which controls the error probabilities when all the parameters (treatments) are equal and which maximize the infimum of the probability of a correct selection over some preference parameter space, simultaneously. Some examples are provided to illustrate the optimal subset selection rule and its interpretation in terms of the 'identified' hypotheses. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1981
Accession Number
ADA101922

Entities

People

  • Deng Yuang Huang
  • Shanti Gupta

Organizations

  • Purdue University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Analysis Of Variance
  • Hypotheses
  • Identification
  • Mathematical Analysis
  • Military Research
  • Normal Distribution
  • Probability
  • Probability Distributions
  • Random Variables
  • Statistical Analysis
  • Statistics
  • Two Dimensional
  • United States
  • United States Government
  • Universities

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.

Technology Areas

  • Space