COMPOSITE FORECASTING WITH DIRICHLET PRIORS Academic Article

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. Copyright 1988, Wiley Blackwell. All rights reserved

authors

• Bessler, David

published proceedings

• DECISION SCIENCES

author list (cited authors)

• BESSLER, D. A., & CHAMBERLAIN, P. J.

citation count

• 12

complete list of authors

• BESSLER, DA||CHAMBERLAIN, PJ

publication date

• December 1988

publisher

• Wiley  Publisher

published in

• Decision Sciences  Journal

Digital Object Identifier (DOI)

• 10.1111/j.1540-5915.1988.tb00302.x

start page

• 771

end page

• 781

volume

• 19

issue

• 4

URL

• http://dx.doi.org/10.1111/j.1540-5915.1988.tb00302.x