Modified cross-validation in semiparametric regression models with dependent errors

被引：16

作者：

Aneiros-Pérez, G ^{[1
]}

Quintela-del-Rio, A ^{[1
]}

机构：

[1] Univ A Coruna, Fac Informat, Dept Matemat, La Coruna 15071, Spain

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2001年 / 30卷 / 02期

关键词：

partial linear models; kernel smoothing; bandwidth selection; mixing;

D O I：

10.1081/STA-100002032

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 study here a modified cross-validation method to choose the smoothing parameter in a partial linear model with dependent errors. The main results are: (i) asymptotic equivalence of ASE and MASE, and (ii) asymptotic optimality of this selector.

引用

页码：289 / 307

页数：19

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