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Management Science Vol. 23 No. 3 1976

Proximal Decision Analysis with Imperfect Information

Carson E. Agnew

Mathematica, Inc.

Abstract

In proximal decision analysis the value of a decision depends on a vector of state variables s and a vector of decision variables d in a quadratic fashion. Suppose some data, represented by a vector x, can be obtained. This paper describes a technique for using the data and develops an expression for the value of the information conveyed by the data. Because the value model is quadratic the data processing procedure uses a linear minimum-variance estimate of the conditional mean of s which depends only on the prior moments of the state vector and the noise associated with the measurement.

DOI
10.1287/mnsc.23.3.275
Volume
23
Issue
3
Pages
275-279
Language
en
Sources
bibtex:phds-export.bib openalex crossref

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