An improved class of estimators for the population mean

被引：22
|
作者：
Diana, Giancarlo [2 ]
Giordan, Marco [2 ]
Perri, Pier Francesco [1 ]
机构：
[1] Univ Calabria, Dept Econ & Stat, I-87036 Arcavacata Di Rende, Italy
[2] Univ Padua, Dept Stat Sci, I-35121 Padua, Italy
来源：
STATISTICAL METHODS AND APPLICATIONS | 2011年 / 20卷 / 02期
关键词：
Rao estimator; Regression estimator; Monte Carlo simulation; Efficiency comparisons; REGRESSION TYPE ESTIMATOR; PRODUCT-TYPE ESTIMATORS; AUXILIARY INFORMATION; RATIO ESTIMATORS;
D O I：
10.1007/s10260-010-0156-6
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：
Starting from the Rao (Commun Stat Theory Methods 20:3325-3340, 1991) regression estimator, we propose a class of estimators for the unknown mean of a survey variable when auxiliary information is available. The bias and the mean square error of the estimators belonging to the class are obtained and the expressions for the optimum parameters minimizing the asymptotic mean square error are given in closed form. A simple condition allowing us to improve the classical regression estimator is worked out. Finally, in order to compare the performance of some estimators with the regression one, a simulation study is carried out when some population parameters are supposed to be unknown.
引用
收藏
页码：123 / 140
页数：18
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