Forecasting product sales with dynamic linear mixture models

Authors:
Phillip M. Yelland;Eunice Lee
Affiliations:
Sun Microsystems Laboratories, Mountain View, California;Sun Microsystems Inc. WorldWide Operations, Newark, California
Venue:
Forecasting product sales with dynamic linear mixture models
Year:
2003

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Abstract

This paper discusses investigations undertaken at Sun Microsystems, Inc. into practical forecasting applications of the Bayesian Dynamic Linear Models described in the seminal work of West and Harrison (1997). Particular emphasis is placed on the use of class II mixture models, which use Bayesian model averaging to help accommodate model uncertainty.