Consistency and Normality of M-Estimators in Partly Linear Models with Stochastic Adapted Errors

被引：0

作者：

Yan, Li ^{[1
]}

Chen, Xia ^{[1
]}

机构：

[1] Shaanxi Normal Univ, Coll Math & Informat Sci, Xian 710062, Peoples R China

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2012年 / 41卷 / 09期

基金：

中国国家自然科学基金;

关键词：

Piecewise polynomial; Partly linear model; M-estimator; Stochastic adapted sequence; STRONG LIMIT-THEOREMS; SEMIPARAMETRIC MODEL; LONGITUDINAL DATA; RANDOM-VARIABLES; RATES; CONVERGENCE; SEQUENCES;

D O I：

10.1080/03610926.2012.657329

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 robust M-estimators for the partly linear model under stochastic adapted errors are considered. It is shown that the M-estimator of parameter is asymptotically normal and the M-estimator of the nonparametric function achieves the optimal rate of convergence for nonparametric regression. Some known results are improved and generalized. Some simulations and a real data example are conducted to illustrate the proposed method.

引用

页码：1557 / 1568

页数：12

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