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Composite Forecasting with Dirichlet Priors *
Author(s) -
Bessler David A.,
Chamberlain Peter J.
Publication year - 1988
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5915.1988.tb00302.x
Subject(s) - dirichlet distribution , prior probability , multinomial distribution , dirichlet process , bayesian probability , computer science , perspective (graphical) , realization (probability) , econometrics , prior information , mathematical optimization , artificial intelligence , mathematics , statistics , mathematical analysis , boundary value problem
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.