On Combining Selection and Estimation in the Search for the Largest Binomial Parameter

Abstract

For k > or = independent binomial populations, from which X sub; approx. = B (ni theta sub;) i = 1,...,k, have been observed, the problem of selecting the population with the largest theta-value and simultaneously estimating the theta-parameter of the selected population is considered. Under several loss functions, Bayes decision rules are derived and studied for independent Beta-priors. A fixed sample size look ahead procedure is also considered. A numerical example is given to illustrate the performance of the procedures.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1990
Accession Number
ADA226595

Entities

People

  • Klaus J. Miescke
  • Shanti Gupta

Organizations

  • Purdue University

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Additives (Chemicals)
  • Binomials
  • Computer Programs
  • Computers
  • Illinois
  • Inequalities
  • Intervals
  • Literature
  • Military Research
  • Observation
  • Permutations
  • Precision
  • Probability
  • Random Variables
  • Sampling
  • Universities

Fields of Study

  • Mathematics

Readers

  • Analytical Mechanics
  • Regression Analysis.

Technology Areas

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