Variable Selection by Stepwise Slicing in Nonparametric Regression

被引：0

作者：

Nong, Jifu ^{[1
]}

机构：

[1] Guangxi Univ Nationalities, Coll Math & Comp Sci, Nanning 530006, Peoples R China

来源：

INTERNATIONAL JOINT CONFERENCE ON COMPUTATIONAL SCIENCES AND OPTIMIZATION, VOL 1, PROCEEDINGS | 2009年

关键词：

D O I：

10.1109/CSO.2009.304

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this paper, variable selection issue is considered in a nonparametric regression setting. Two stepwise procedures based on variance estimators are proposed for selecting the significant variables in a general nonparametric regression model. These procedures do not require multidimensional smoothing at intermediate steps and they are based on formal rests of hypotheses as opposed to existing methods in the literature. Asymptotic properties are examined and empirical results are given.

引用

页码：430 / 433

页数：4

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