Title: A sensitivity analysis procedure for Bayesian decision-making

Authors: Faizul Huq, Clarence 'Red' Martin, Ken Cutright, Trevor S. Hale

Addresses: Department of Management Systems, Ohio University, Athens, Ohio 45701, USA; Groupe ESC Pau, 3 rue Saint-John Perse, Pau 64000, France. ' Department of Management Systems, Ohio University, Athens, Ohio 45701, USA. ' Department of Management Systems, Ohio University, Athens, Ohio 45701, USA. ' Department of Management, Marketing and Business Administration, University of Houston – Downtown, Houston, Texas 77002, USA

Abstract: In an effort to see how analytical model outputs change with respect to variations in model inputs, sensitivity analysis procedures have been widely used in applications such as mathematical programming and classical optimisation. However, until recently, sensitivity analysis has seen only limited application in the area of decision theory and support. This paper investigates the use of sensitivity analysis in the realm of classical Bayesian reasoning, where the probabilities of the states of nature are revised based on additional information. These updated probabilities only become useful, however, if they lead to an optimal decision different from that obtained on the basis of prior probabilities. This paper develops a novel sensitivity analysis procedure for Bayesian decision-making and proposes a set of criteria for the ranges of the model input parameters over which the current solution will remain optimal.

Keywords: decision support; sensitivity analysis; Bayesian decision making; Bayesian reasoning; model input parameters; optimisation.

DOI: 10.1504/IJDSRM.2009.027244

International Journal of Decision Sciences, Risk and Management, 2009 Vol.1 No.1/2, pp.23 - 35

Published online: 18 Jul 2009 *

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