A novel improved class of ratio-product type exponential estimators of population variance

Document Type : Article

Authors

1 School of Mathematical Sciences, Institute of Statistics, Zhejiang University, Hangzhou 310058, China

2 - Department of Statistics, Faculty of Physical Sciences, Government College University Faisalabad, Allama Iqbal Road, Faisalabad 38000, Pakistan. - School of Mathematical Sciences, Shanghai Jiao Tong University, Minhang Campus, 800 Dongchuan Road, Shanghai 200240, China.

3 Department of Statistics, Faculty of Physical Sciences, Government College University Faisalabad, Allama Iqbal Road, Faisalabad 38000, Pakistan

Abstract

Several auxiliary information-based estimators of the population variance are available in the existing literature of survey sampling. Mostly, these estimators are based on conventional dispersion measures of the auxiliary variable. In this study, a generalized class of ratio-product type exponential estimators of the population variance is proposed which integrates the auxiliary information on non-conventional dispersion measures under simple random sampling in the ratio-type exponential class of estimators. The performance of the proposed estimators is compared, theoretically and numerically, with the several existing estimators of the population variance. It is established that the proposed class of estimators outperforms the existing estimators in terms of the lower mean square and relative root mean square errors. Moreover, the percentage relative efficiency of the proposed estimators is much higher as compared to their counterparts.

Keywords

References

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Scientia Iranica
Volume 29, Issue 4
Transactions on Industrial Engineering (E)
July and August 2022
Pages 2115-2133

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