Optimum Two-Stage Selection Procedures for Weibull Populations.

Abstract

LET PI,...,PIK BE Weibull populations with a common known shape parameter, and with unknown scale parameters. The goal is to find the population with the largest scale parameter. From each population, Type II-censored observations are available at two stages, where censoring at stage 1 occurs at the q-th (r-th) failure. Two-stage procedures with screening at the first stage are considered which are optimum permutation invariant in terms of the risk with respect to a large class of loss functions. For the procedure with a fixed subset size at stage 1, the least favorable parameter configuration under the indifference zone approach is of the slippage type, which makes it feasible to control the infimum of the probability of a correct selection. Some extensions of the results are discussed at the end. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1985
Accession Number
ADA162824

Entities

People

  • Klaus J. Miescke
  • Shanti Gupta

Organizations

  • Purdue University

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Air Force
  • Contracts
  • Convolution
  • Illinois
  • Military Research
  • Observation
  • Permutations
  • Probability
  • Random Variables
  • Sampling
  • Scientific Research
  • Statistics
  • Universities

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.
  • Statistical inference.

Technology Areas

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