Title of article
A novel improved class of ratio-product type exponential estimators of population variance
Author/Authors
Naz, F School of Mathematical Sciences - Institute of Statistics - Zhejiang University - Hangzhou, China , Nawaz, T Department of Statistics - Faculty of Physical Sciences - Government College University Faisalabad - Allama Iqbal Road - Faisalabad, Pakistan , Abid, M Department of Statistics - Faculty of Physical Sciences - Government College University Faisalabad - Allama Iqbal Road - Faisalabad, Pakistan , Pang, T School of Mathematical Sciences - Institute of Statistics - Zhejiang University - Hangzhou, China
Pages
19
From page
2115
To page
2133
Abstract
Abstract. Several auxiliary information-based estimators of population variance are available in the existing literature on 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 by integrating the nonconventional auxiliary information under Simple Random Sampling (SRS). The performance of the proposed estimators was compared, theoretically and numerically, with several existing estimators of the population variance. It was established that the proposed class of estimators outperformed the existing estimators in terms of Mean Squared Error (MSE) and Relative Root Mean Square Error (RRMSE). Moreover, Percentage Relative Effciency (PRE) of the proposed estimators was much higher than that of their counterparts.
Keywords
Simple random sampling , Auxiliary variable , Mean square error , Percentage relative effciency , Relative root mean square error
Journal title
Iranian Journal of Accounting, Auditing and Finance (IJAAF)
Serial Year
2022
Record number
2732055
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