It is widely recognized that Bayes decision analysis with gamma variables leads almost invariably to fairly troublesome computational difficulties. The purpose of this paper is to show how these difficulties can be circumvented by the use of certain results of decision theory in conjunction with some specialized developments on series expansions. Specifically, the posterior law will be approximated by the computationally and analytically convenient bivariate normal distribution. The approximation technique derived here is compared to exact formulas through statistical measures as well as comparative performance in water resource management contexts.
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