A small sample estimator for a polynomial regression with errors in the variables

被引：23
|
作者：
Cheng, CL
Schneeweiss, H
Thamerus, M
机构：
[1] Univ Munich, Seminar Okonometrie & Stat, D-80799 Munich, Germany
[2] Acad Sinica, Taipei 115, Taiwan
[3] Bayer Landesanstalt Tierzucht, Munich, Germany
来源：
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY | 2000年 / 62卷
关键词：
adjusted least squares; measurement error; modified adjusted least squares; polynomial regression; small sample properties;
D O I：
10.1111/1467-9868.00258
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：
An adjusted least squares estimator, introduced by Cheng and Schneeweiss for consistently estimating a polynomial regression of any degree with errors in the variables, is modified such that it shows good results in small samples without losing its asymptotic properties for large samples. Simulation studies corroborate the theoretical findings.
引用
收藏
页码：699 / 709
页数：11
相关论文
共 50 条
12345