Optimal Sampling in Selection Problems.

Abstract

This paper describes several optimal sampling problems that arise in connection with selection and ranking procedures. A selection procedure typically consists of three ingredients: (1) a sampling rule, (2) a stopping rule, and (3) a decision rule, though these components are not usually explicitly so labeled. The problem of optimal sampling arises in different ways depending on the context of the problem at hand. Broadly speaking, the problem of optimal (or optimum) sampling arises because of the need for balancing between the cost of sampling and the cost of making a wrong decision. Obviously, increasing the amount of sampling increases the former cost while decreasing the latter.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1983
Accession Number
ADA130248

Entities

People

  • Shanti Gupta

Organizations

  • Purdue University

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Clinical Trials
  • Data Science
  • Decision Theory
  • Governments
  • Information Science
  • Military Research
  • Multivariate Analysis
  • New York
  • North Carolina
  • Probability
  • Random Variables
  • Sampling
  • Statistical Decision Theory
  • Statistics
  • United States
  • United States Government
  • Universities

Readers

  • Economics
  • Mathematical Modeling and Probability Theory.
  • Regression Analysis.