Model selection and randomization for weakly dependent time series forecasting

Wintenberger, Olivier; Alquier, Pierre

Wintenberger, Olivier; Alquier, Pierre (2009), Model selection and randomization for weakly dependent time series forecasting, 41èmes Journées de Statistique, SFdS, Bordeaux, 2009, Bordeaux, France, France

Type

Communication / Conférence

External document link

http://hal.inria.fr/inria-00386733/en/

Date

2009

Conference title

41èmes Journées de Statistique, SFdS, Bordeaux

Conference date

2009

Conference city

Bordeaux, France

Conference country

France

Metadata

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Author(s)

Wintenberger, Olivier
Alquier, Pierre

Abstract (EN)

Observing a stationary time series, we propose in this paper new two steps procedures for predicting the next value of the time series. Following machine learning theory paradigm, the first step consists in determining randomized estimators, or "experts", in (possibly numerous) different predictive models. In the second step estimators are obtained by model selection or randomization associated with exponential weights of these experts. We prove Oracle inequalities for both estimators and provide some applications for linear, artificial Neural Networks and additive non-parametric predictors.

Subjects / Keywords

Statistics