Proximal Decision Analysis with Imperfect Information

Carson E. Agnew
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Carson E. Agnew: Mathematica, Inc.

Management Science, 1976, vol. 23, issue 3, 275-279

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.

Date: 1976
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:23:y:1976:i:3:p:275-279

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