An improved efficient class of estimators for the population variance

被引：9

作者：

Niaz, Iqra ^{[1
]}

Sanaullah, Aamir ^{[1
]}

Saleem, Iram ^{[2
]}

Shabbir, Javid ^{[3
]}

机构：

[1] COMSATS Univ Islamabad, Dept Stat, Lahore Campus, Lahore, Pakistan

[2] Forman Christian Coll Lahore, Dept Stat, Lahore, Pakistan

[3] Quaid I Azam Univ Islamabad, Dept Stat, Islamabad, Pakistan

来源：

CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE | 2022年 / 34卷 / 04期

关键词：

auxiliary information; bias; finite population variance; mean squared error; usual linear regression; EXPONENTIAL ESTIMATOR; ESTIMATION STRATEGY; RATIO;

D O I：

10.1002/cpe.6620

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

In this article, we propose an improved class of estimators for a finite population variance in presence of the auxiliary information. The expressions of the bias and mean squared error of the proposed class of estimators are obtained up to the first order of approximation. The conditions under which the proposed class of estimators is more efficient than the other estimators have also been derived. It is observed from the simulation results that the proposed class of estimators is more efficient than the usual linear regression estimator.

引用

页数：15

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