SOME ORDER STATISTICS RELATING TO MARKOV CHAINS: AN APPLICATION TO PURCHASING POLICIES,

Abstract

A special instance of the general problem of decision-making under uncertainty is condidered. In the absence of a well-defined utility function, the following method is adopted: First, a reasonable or acceptable policy is chosen with unspecified parameters. Then, the associated decision rule is formulated; typically, these are functional transforms of appropiate state variables. Analysis is made of the outcomes produced by the rule in conjunction with the stochastic price process. Finally, some functionals of the (random) outcomes are computed with a view to obtain measures of performance of the decision rule. In each case, the derivations indicate the dependence of the measures (of performance) on the unspecified parameters. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1944
Accession Number
AD0433690

Entities

People

  • Jose Trevino
  • Surojeet Sengupta

Organizations

  • Case Western Reserve University

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Computing-Related Activities
  • Data Science
  • Information Science
  • Markov Chains
  • Mathematics
  • Order Statistics
  • Statistics
  • Uncertainty

Fields of Study

  • Mathematics

Readers

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