Two-stage model selection procedures in partially linear regression

被引：18

作者：

Bunea, F ^{[1
]}

Wegkamp, MH ^{[1
]}

机构：

[1] Florida State Univ, Dept Stat, Tallahassee, FL 32306 USA

来源：

CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE | 2004年 / 32卷 / 02期

关键词：

adaptive minimax estimation; consistent covariate selection; oracle inequality; partially linear regression;

D O I：

10.2307/3315936

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：

The authors propose a two-stage estimation procedure for the partially linear model Y = f(0) (T) + X'beta(0) + epsilon. They show how to estimate consistently the location of the nonzero components of beta(0). Their approach turns out to be compatible with minimax adaptive estimation of f(0) over Besov balls in the case of penalized least squares. Their proofs are based on a new type of oracle inequality.

引用

页码：105 / 118

页数：14

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