Regression function estimation as a partly inverse problem - Archive ouverte HAL
Article Dans Une Revue Annals of the Institute of Statistical Mathematics Année : 2020

Regression function estimation as a partly inverse problem

Résumé

This paper is about nonparametric regression function estimation. 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 most previous results. Upper and lower bounds for resulting rates are provided.
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Dates et versions

hal-01690856 , version 1 (23-01-2018)
hal-01690856 , version 2 (05-04-2018)
hal-01690856 , version 3 (11-07-2018)
hal-01690856 , version 4 (18-10-2018)

Identifiants

  • HAL Id : hal-01690856 , version 4

Citer

Fabienne Comte, Valentine Genon-Catalot. Regression function estimation as a partly inverse problem. Annals of the Institute of Statistical Mathematics, 2020, 72 (4), pp.1023-1054. ⟨hal-01690856v4⟩
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