Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/1192
Title: Forecasting using belief functions: An application to marketing econometrics
Authors: Kanjanatarakul O.
Sriboonchitta S.
Denoeux T.
Issue Date: 2014
Publisher: Elsevier Inc.
Abstract: A method is proposed to quantify uncertainty on statistical forecasts using the formalism of belief functions. The approach is based on two steps. In the estimation step, a belief function on the parameter space is constructed from the normalized likelihood given the observed data. In the prediction step, the variable Y to be forecasted is written as a function of the parameter θ and an auxiliary random variable Z with known distribution not depending on the parameter, a model initially proposed by Dempster for statistical inference. Propagating beliefs about θ and Z through this model yields a predictive belief function on Y. The method is demonstrated on the problem of forecasting innovation diffusion using the Bass model, yielding a belief function on the number of adopters of an innovation in some future time period, based on past adoption data. © 2014 Elsevier B.V. All rights reserved.
URI: http://www.scopus.com/inward/record.url?eid=2-s2.0-84899915661&partnerID=40&md5=8648ff3b49dc5376265577730efcbe50
http://cmuir.cmu.ac.th/handle/6653943832/1192
ISSN: 0888613X
Appears in Collections:ECON: Journal Articles

Files in This Item:
There are no files associated with this item.


Items in CMUIR are protected by copyright, with all rights reserved, unless otherwise indicated.