Regression function estimation as a partly inverse problem

被引：0
作者：
F. Comte
V. Genon-Catalot
机构：
[1] University Paris Descartes,MAP5 UMR CNRS 8145
来源：
Annals of the Institute of Statistical Mathematics | 2020年 / 72卷
关键词：
Hermite basis; Laguerre basis; Model selection; Nonparametric estimation; Regression function;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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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页码：1023 / 1054
页数：31
相关论文
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