Efficient estimation of additive nonparametric regression models

被引：95

作者：

Linton, OB

机构：

[1] Cowles Foundation for Research in Economics, Yale University, New Haven

来源：

BIOMETRIKA | 1997年 / 84卷 / 02期

关键词：

additive regression models; backfitting; dimensionality reduction; Kernel estimation; nonparametric regression;

D O I：

10.1093/biomet/84.2.469

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

We define a new procedure for estimating additive nonparametric regression models. We use the integration method of Linton & Nielsen (1995) to provide starting values that are then used in a one-step backfitting procedure. We show that our new method is efficient in a certain sense and dominates the straight integration method according to mean squared error.

引用

页码：469 / 473

页数：5

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BUJA A, 1989, ANN STAT, V17, P453, DOI 10.1214/aos/1176347115

[3]

Cox D.R., 1974, THEORETICAL STAT

[4] DESIGN-ADAPTIVE NONPARAMETRIC REGRESSION [J].