On Bayes and Empirical Bayes Procedures for Selection Problems

Abstract

This paper describes selection and ranking procedures using Bayesian or Empirical Bayes approaches. Section 2 of this paper deals with the problem of selecting the best population or selecting a subset containing the best population through Bayesian approach. An essentially complete class is obtained for a class of reasonable loss functions. A control condition, called P* - condition, is used to filter out poor procedures. Section 3 set up a general formation of empirical Bayes framework for selection problems. Several empirical Bayes frameworks are discussed based on the underlying statistical models. Two selection problems dealing with binomial and uniform distributions are discussed in detail.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1986
Accession Number
ADA174159

Entities

People

  • Shanti Gupta
  • Tachen Liang

Organizations

  • Purdue University

Tags

Communities of Interest

  • C4I
  • Human Systems

DTIC Thesaurus Topics

  • Bayesian Inference
  • Bayesian Networks
  • Computations
  • Data Science
  • Decision Theory
  • Estimators
  • Information Science
  • New York
  • Probability
  • Probability Density Functions
  • Random Variables
  • Statistical Analysis
  • Statistical Decision Theory
  • Statistical Inference
  • Statistics
  • Theorems
  • United States

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Business Analytics
  • Regression Analysis.

Technology Areas

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