Estimation of nonparametric regression models by wavelets

被引：1

作者：

Morettin, Pedro A. ^{[1
]}

Porto, Rogerio F. ^{[2
]}

机构：

[1] Univ Sao Paulo, Sao Paulo, Brazil

[2] Bank Brazil, Brasilia, DF, Brazil

来源：

SAO PAULO JOURNAL OF MATHEMATICAL SCIENCES | 2022年 / 16卷 / 01期

基金：

巴西圣保罗研究基金会;

关键词：

Regression models; Nonparametric; Wavelets; RANDOM DESIGN; SHRINKAGE;

D O I：

10.1007/s40863-021-00240-5

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

In this paper we survey the estimation of nonparametric regression models using wavelets, under different conditions on the innovations, on the predictor variables, on the function spaces involved and on the regularity conditions imposed. We begin with the seminal works of Donoho and co-authors, in the regular fixed design and independent and identically Gaussian noise and move towards non-regular designs, random designs and correlated errors.

引用

页码：539 / 565

页数：27

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