Exploratory Quantitative Analysis of Emergent Problems with Scant Information

Tim Bedford
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Tim Bedford: University of Strathclyde

Chapter 14 in Making Essential Choices with Scant Information, 2009, pp 279-300 from Palgrave Macmillan

Abstract: Abstract This chapter compares and contrasts three methods for handling quantitative decision analysis when information is limited: Bayesian Robustness, Bayes Linear and Minimum Information. The way they utilize partial model specification from experts and their potential use as an exploratory tool is considered. The possibility of carrying out sensitivity analysis with these methods is explored and the recommendation made that this type of analysis is useful in extending the small world scope of such decision analyses to include various potential control mechanisms. The discussion is illustrated by simple examples.

Keywords: Prior Distribution; Expected Utility; Analyse Information; Minimum Information; Maximum Entropy Principle (search for similar items in EconPapers)
Date: 2009
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Persistent link: https://EconPapers.repec.org/RePEc:pal:palchp:978-0-230-23683-7_14

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DOI: 10.1057/9780230236837_14

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