Variance estimation in nonparametric multiple regression

被引：7
|
作者：
Kulasekera, KB
Gallagher, C
机构：
[1] Clemson Univ, Dept Math Sci, Clemson, SC 29634 USA
[2] Calif State Univ Los Angeles, Dept Math & Stat, Chico, CA 95929 USA
来源：
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2002年 / 31卷 / 08期
关键词：
nonparametric regression surface; difference method; asymptotic distribution; sparse design;
D O I：
10.1081/STA-120006074
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
We consider the variance estimation in a general nonparametric regression model with multiple covariates. We extend difference methods to the multivariate setting by introducing an algorithm that orders the design points in higher dimensions. We also consider an adaptive difference estimator which requires much less strict assumptions on the covariate design and can significantly reduce mean squared error for small sample sizes.
引用
收藏
页码：1373 / 1383
页数：11
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