Semi-parametric estimation of shifts

Abstract : We observe a large number of functions differing from each other only by a translation parameter. While the main pattern is unknown, we propose to estimate the shift parameters using $M$-estimators. Fourier transform enables to transform this statistical problem into a semi-parametric framework. We study the convergence of the estimator and provide its asymptotic behavior. Moreover, we use the method in the applied case of velocity curve forecasting.
Type de document :
Pré-publication, Document de travail
Published in at http://dx.doi.org/10.1214/07-EJS026 the Electronic Journal of Statistics (http://.. 2007
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https://hal.archives-ouvertes.fr/hal-00347905
Contributeur : Jean-Michel Loubes <>
Soumis le : mercredi 17 décembre 2008 - 09:54:10
Dernière modification le : mercredi 31 octobre 2018 - 01:16:14

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  • HAL Id : hal-00347905, version 1
  • ARXIV : 0712.1936

Citation

Fabrice Gamboa, Jean-Michel Loubes, Elie Maza. Semi-parametric estimation of shifts. Published in at http://dx.doi.org/10.1214/07-EJS026 the Electronic Journal of Statistics (http://.. 2007. 〈hal-00347905〉

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