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Prévision d'un processus à valeurs fonctionnelles en présence de non stationnarités. Application à la consommation d'électricité

Abstract : We study here the problem of predicting a functional valued stochastic process. We first explore the model proposed by Antoniadis et al. (2006) in the context of a practical application -the french electrical power demand- where the hypothesis of stationarity may fail. The departure from stationarity is twofold: an evolving mean level and the existence of groups that may be seen as classes of stationarity. We explore some corrections that enhance the prediction performance. The corrections aim to take into account the presence of these nonstationary features. In particular, to handle the existence of groups, we constraint the model to use only the data that belongs to the same group of the last available data. If one knows the grouping, a simple post-treatment suffices to obtain better prediction performances.
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https://hal.inria.fr/hal-00778121
Contributor : Erwan Le Pennec <>
Submitted on : Friday, January 18, 2013 - 5:32:38 PM
Last modification on : Tuesday, July 6, 2021 - 3:39:41 AM

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  • HAL Id : hal-00778121, version 1

Citation

Anestis Antoniadis, Xavier Brossat, Jairo Cugliari, Jean-Michel Poggi. Prévision d'un processus à valeurs fonctionnelles en présence de non stationnarités. Application à la consommation d'électricité. Journal de la Société Française de Statistique, Société Française de Statistique et Société Mathématique de France, 2012, 153 (2), pp.57-78. ⟨hal-00778121⟩

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