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Forecasting with k-factor Gegenbauer Processes: Theory and Applications


  • Laurent Ferrara

    (Centre d'Observation Economique - Chambre de Commerce et d'Industrie de Paris)

  • Dominique Guegan

    (Département Mathématiques Mécanique et Informatique - URCA - Université de Reims Champagne-Ardenne)


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.

Suggested Citation

  • Laurent Ferrara & Dominique Guegan, 2001. "Forecasting with k-factor Gegenbauer Processes: Theory and Applications," Post-Print halshs-00193667, HAL.
  • Handle: RePEc:hal:journl:halshs-00193667
    DOI: 10.1002/for.815
    Note: View the original document on HAL open archive server:

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