Forecasting with k-Factor Gegenbauer Processes: Theory and Applications
Laurent Ferrara and
Dominique Guegan
Journal of Forecasting, 2001, vol. 20, issue 8, 581-601
Abstract:
This paper deals with the k-factor extension of the long memory Gegenbauer process proposed by Gray et al. (1989). We give the analytic expression of the prediction function derived from this long memory process and provide the h-step-ahead prediction error when parameters are either known or estimated. We investigate the predictive ability of the k-factor Gegenbauer model on real data of urban transport traffic in the Paris area, in comparison with other short- and long-memory models. Copyright © 2001 by John Wiley & Sons, Ltd.
Date: 2001
References: Add references at CitEc
Citations: View citations in EconPapers (61)
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
Working Paper: Forecasting with k-factor Gegenbauer Processes: Theory and Applications (2001)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:jof:jforec:v:20:y:2001:i:8:p:581-601
Access Statistics for this article
Journal of Forecasting is currently edited by Derek W. Bunn
More articles in Journal of Forecasting from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley-Blackwell Digital Licensing () and Christopher F. Baum ().