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Decision Analytica: An Example of Bayesian Inference and Decision Theory Using Mathematica

In: Economic and Financial Modeling with Mathematica®

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  • Robert J. Korsan

Abstract

Decision analysis is a blending of four ingredients. First, subjective probability theory is used to describe a decision maker’s “a priori” uncertainty (degree of belief) about the outcomes of some event(s). Second, Bayesian inference is used to determine the appropriate “a posteriori” uncertainty given the revelation of some evidence. Third, utility theory is used to describe the decision maker’s values in a consistent, mathematically manipulable fashion. Fourth and finally, decision theory is used to determine the “optimal” strategy, i.e. the sequence of event-contingent actions which lead to the highest valued outcomes given the decision maker’s values.

Suggested Citation

  • Robert J. Korsan, 1993. "Decision Analytica: An Example of Bayesian Inference and Decision Theory Using Mathematica," Springer Books, in: Hal R. Varian (ed.), Economic and Financial Modeling with Mathematica®, chapter 17, pages 407-458, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4757-2281-9_17
    DOI: 10.1007/978-1-4757-2281-9_17
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