On Gamma-Minimax, Minimax, and Bayes Procedures for Selecting Populations Close to a Control.

Abstract

Let Pi sub 0, Pi sub 1,...,Pi sub k be (k+1) normally distributed populations and let Pi sub 0 be a control population. Our goal is to select those populations which are sufficiently close to the control in terms of the (unknown) means of the populations. A zero-one type loss function is defined. Gamma-minimax rules, Bayes rules and minimax rules are derived for this problem and compared. Some optimal properties of Gamma-minimax rules are shown; also Gamma-minimax rules are derived for distributions other than the normal.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1980
Accession Number
ADA096094

Entities

People

  • Ping Hsiao
  • Shanti Gupta

Organizations

  • Purdue University

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Binomials
  • Continents
  • Contracts
  • Geographic Regions
  • Governments
  • Industrial Production
  • Mathematics
  • Military Research
  • New York
  • North America
  • Notation
  • Observation
  • Statistics
  • Tank Guns
  • Universities

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.
  • Research Science/Academic Research

Technology Areas

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