An Application of Empirical Bayes Techniques to the Simultaneous Estimation of Many Probabilities

Abstract

This document considers the following situation: each of N different combat units is presented with a number of requirements to satisfy, each requirement being classified into one of K mutually exclusive categories. For each unit satisfying and requirement in that category is desired. The problem can be generally stated as that of estimating N different K-dimensional vectors of probabilities based upon a corresponding set of K-dimensional vectors of sample proportions. An empirical Bayes model is formulated and applied to an example from the Marine Corps Combat Readiness Evaluation System (MCCRES). The EM algorithm provides a convenient method of estimating the prior parameters. The Bayes estimates are compared to the ordinary estimates, i.e. the sample proportions, by means of cross-validation and the Bayes estimates are shown to provide considerable improvement. (Author)

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Document Details

Document Type
Technical Report
Publication Date
May 03, 1984
Accession Number
ADA141985

Entities

People

  • S. S. Brier
  • S. Zacks
  • W. H. Marlow

Organizations

  • George Washington University

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Algorithms
  • Classification
  • Combat Readiness
  • Contracts
  • Data Analysis
  • Data Science
  • Engineering
  • Estimators
  • Information Science
  • Marine Corps
  • Military Research
  • Probability
  • Random Variables
  • Security
  • Test And Evaluation
  • Validation
  • Warfare

Fields of Study

  • Mathematics

Readers

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  • Psychometric Testing or Psychological Assessment.