Regression function estimation on non compact support as a partly inverse problem

Abstract : This paper is about nonparametric regression function estimation, first in the independent setting and in a second stage, in the context of an autoregressive model or of discrete time observation of a diffusion process, both settings corresponding to dependent variables. Our estimator is a one step projection estimator obtained by least-squares contrast minimization. The specificity of our work is to consider a new model selection procedure including a cutoff for the underlying matrix inversion, and to provide theoretical risk bounds that apply to non compactly supported bases, a case which was specifically excluded of all previous results. Upper and lower bounds for new rates are provided.
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Pré-publication, Document de travail
MAP5 2018-01. 2018
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https://hal.archives-ouvertes.fr/hal-01690856
Contributeur : Fabienne Comte <>
Soumis le : jeudi 5 avril 2018 - 11:53:11
Dernière modification le : samedi 7 avril 2018 - 01:12:53

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NewNonCompactReg.pdf
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  • HAL Id : hal-01690856, version 2

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Fabienne Comte, V Genon-Catalot. Regression function estimation on non compact support as a partly inverse problem. MAP5 2018-01. 2018. 〈hal-01690856v2〉

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