The efficiency of the second-order nonlinear least squares estimator and its extension

被引：11

作者：

Kim, Mijeong ^{[1
]}

Ma, Yanyuan ^{[1
]}

机构：

[1] Texas A&M Univ, Dept Stat, College Stn, TX 77843 USA

来源：

ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS | 2012年 / 64卷 / 04期

关键词：

Second-order least squares estimator; Heteroscedasticity; Moments; Semiparametric methods; SEMIPARAMETRIC ESTIMATORS; REGRESSION-MODELS;

D O I：

10.1007/s10463-011-0332-y

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 revisit the second-order nonlinear least square estimator proposed in Wang and Leblanc (Anne Inst Stat Math 60:883-900, 2008) and show that the estimator reaches the asymptotic optimality concerning the estimation variability. Using a fully semiparametric approach, we further modify and extend the method to the heteroscedastic error models and propose a semiparametric efficient estimator in this more general setting. Numerical results are provided to support the results and illustrate the finite sample performance of the proposed estimator.

引用

页码：751 / 764

页数：14

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