Composite Forecasting with Dirichlet Priors*

David A. Bessler · Peter Chamberlain

53 citations0/0 files storedDecision Sciences

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Forecasting Techniques and Applications Probability and Statistical Research Statistical Methods and Bayesian Inference

Abstract

ABSTRACT In this paper, composite forecasting is considered from a Bayesian perspective. A forecast user combines two or more forecasts of an operationally relevant random variable. We consider the case where outperformance is modeled as a realization from a multinomial process. The user has prior beliefs about the probability that a particular method outperforms all others, information which is summarized by the Dirichlet distribution. An empirical example with hog prices in the United States illustrates the method.

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References

1969The Combination of Forecasts 1984Improved methods of combining forecasts 1967Man as an intuitive statistician.1983Averages of Forecasts: Some Empirical Results 1980Statistical Decision Theory 1986Combining Economic Forecasts 1981Forecasting livestock prices with individual and composite methods

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