On Two-Stage Prodcedures for Finding A Population Better than a Control.

Abstract

A natural class of two-stage procedures is proposed which can be completely described and studied in terms of Neyman-Pearson testing theory, where the unsymmetry of tests, however, can be overcome to a considerable extent. As a typical result it is shown that optimality of tests carries over to optimality of two-stage procedures. Finally, under normality, comparisons are made in case of k = 2 with certain Bayesian procedures.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1980
Accession Number
ADA100950

Entities

People

  • Klaus J. Miescke

Organizations

  • Purdue University

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Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Behavior And Behavior Mechanisms
  • Computing-Related Activities
  • Data Science
  • Information Science
  • Interdisciplinary Science
  • Mathematics
  • Military Research
  • New York
  • Normality
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  • United States
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Fields of Study

  • Mathematics

Readers

  • Aerospace Test and Evaluation
  • Regression Analysis.

Technology Areas

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