TWO EXTENSIONS OF STATISTICAL DECISION THEORY

Abstract

The objective of the project was to develop broader formulations of the mathematical (statistical) theory of decisions. This final report presents two broad scope generalizations which have resulted from the project. The first generalization discussed is a decision-making model which applies to the case of a not-well-informed decision maker with independent data sources. In this model, the inference about the prior distribution is determined from the solution of an adjunct decision problem, which specifies the minimum risk hypothesis in the light of the available information. The second generalization presented is a model of multi-period decision making for both stationary and Markovian environments. In contrast to the model discussed in the above paragraph, this model does not assume independent data sources, i.e., that the observation processes are not affected by the actions of the decision maker.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1965
Accession Number
AD0617082

Entities

People

  • U. O. Gagliardi

Tags

Communities of Interest

  • Human Systems
  • Materials and Manufacturing Processes
  • Weapons Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Air Force
  • Bayes Theorem
  • Computations
  • Computer Programs
  • Computers
  • Contracts
  • Data Science
  • Decision Theory
  • Factor Analysis
  • Information Science
  • Information Systems
  • Probability
  • Procedures (Computers)
  • Security
  • Statistical Analysis
  • Statistical Decision Theory

Readers

  • Mathematical Modeling and Probability Theory.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference