Model selection and randomization for weakly dependent time series forecasting
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
TypeCommunication / Conférence
External document linkhttp://hal.inria.fr/inria-00386733/en/
Conference title41èmes Journées de Statistique, SFdS, Bordeaux
Conference cityBordeaux, France
MetadataShow full item record
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 / KeywordsStatistics
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