Skip to Main content Skip to Navigation
Preprints, Working Papers, ...

Regression function estimation as a partly inverse problem

Abstract : 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.
Complete list of metadatas

Cited literature [21 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01690856
Contributor : Fabienne Comte <>
Submitted on : Thursday, October 18, 2018 - 3:04:47 PM
Last modification on : Friday, April 10, 2020 - 5:24:03 PM
Document(s) archivé(s) le : Saturday, January 19, 2019 - 2:37:15 PM

File

Regression.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01690856, version 4

Collections

Citation

Fabienne Comte, Valentine Genon-Catalot. Regression function estimation as a partly inverse problem. 2018. ⟨hal-01690856v4⟩

Share

Metrics

Record views

170

Files downloads

399