Forecasting with k-factor Gegenbauer Processes: Theory and Applications

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.
Type de document :
Article dans une revue
Journal of Forecasting, Wiley, 2001, 20 (8), pp.581 - 601. 〈10.1002/for.815〉
Liste complète des métadonnées

https://halshs.archives-ouvertes.fr/halshs-00193667
Contributeur : Dominique Guégan <>
Soumis le : mardi 4 décembre 2007 - 12:04:05
Dernière modification le : jeudi 4 octobre 2018 - 18:28:03

Lien texte intégral

Identifiants

Collections

INSMI | INTI | URCA | LMR

Citation

Laurent Ferrara, Dominique Guegan. Forecasting with k-factor Gegenbauer Processes: Theory and Applications. Journal of Forecasting, Wiley, 2001, 20 (8), pp.581 - 601. 〈10.1002/for.815〉. 〈halshs-00193667〉

Partager

Métriques

Consultations de la notice

220