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Proximal Decision Analysis with Imperfect Information

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  • 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.

Suggested Citation

  • Carson E. Agnew, 1976. "Proximal Decision Analysis with Imperfect Information," Management Science, INFORMS, vol. 23(3), pages 275-279, November.
    • Handle: RePEc:inm:ormnsc:v:23:y:1976:i:3:p:275-279
    DOI: 10.1287/mnsc.23.3.275
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