Variable Selection by Stepwise Slicing in Nonparametric Regression

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.

作者: Jifu Nong

作者单位: College of Mathematics and Computer Science Guangxi University for Nationalities Guangxi, Nanning, 530006, China

会议类型: 国际会议

会议名称: The Second International Joint Conference on Computational Science and Optimization(CSO 2009)(2009 国际计算科学与优化会议)

会议地点: 三亚

会议语种:英文

页码: 430-433

在线出版日期: 2009-04-24（万方平台首次上网日期，不代表论文的发表时间）