Locally Optimal Subset Selection Rules Based on Ranks Under Joint Type II Censoring.

Abstract

This paper deals with the derivation of subset selection rules which satisfy the basic P-condition and which locally maximize the probability of a correct selection among all invariant subset selection rules based on the ranks under the joint type II censoring. Following the earlier setup of Gupta, Huang and Nagel (1979), a locally optimal subset selection rule R1 is derived. The property of local monotonicity related to the rule R1 is discussed.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1984
Accession Number
ADA146179

Entities

People

  • Sumedha Gupta
  • T. C. Liang

Organizations

  • Purdue University

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Distribution Functions
  • Governments
  • Intervals
  • Life Tests
  • Military Research
  • Observation
  • Permutations
  • Probability
  • Prototypes
  • Random Variables
  • Statistics
  • United States
  • United States Government
  • Universities

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.
  • Statistical inference.