TY - JOUR ID - 21219 TI - Enhancing efficiency of ratio-type estimators of population variance by a combination of information on robust location measures JO - Scientia Iranica JA - SCI LA - en SN - 1026-3098 AU - Naz, F. AU - Abid, M. AU - Nawaz, T. AU - Pang, T. AD - Department of Mathematics, Institute of Statistics, Zhejiang University, Hangzhou 310027, People’s Republic of China AD - Faculty of Physical Sciences, Department of Statistics, Government College University Faisalabad, Pakistan AD - Faculty of Physical Sciences, Department of Statistics, Government College University Faisalabad, Pakistan. ;School of Mathematical Sciences, Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China. AD - Department of Mathematics, Institute of Statistics, Zhejiang University, Hangzhou 310027, People’s Republic of China. Y1 - 2020 PY - 2020 VL - 27 IS - 4 SP - 2040 EP - 2056 KW - Auxiliary variable KW - Bias KW - Efficiency KW - Mean square error KW - Outliers KW - Ratio estimators DO - 10.24200/sci.2019.5633.1385 N2 - Numerous ratio-type estimators of the population variance are proposed in the existing literature based on different characteristics of the study as well as the auxiliary variable. However, mostly the existing estimators are based on the conventional measures of the population characteristics and their efficiency is dubious in the presence of outliers in the data. This study presents improved families of variance estimators under simple random sampling without replacement assuming that the information on some robust non-conventional location parameters of the auxiliary variable is known besides the usual conventional parameters. The bias and mean square error of the proposed families of estimators are obtained and the efficiency conditions are derived mathematically. The theoretical results are supplemented with the numerical illustrations by using real datasets which indicates the supremacy of the suggested families of estimators. UR - https://scientiairanica.sharif.edu/article_21219.html L1 - https://scientiairanica.sharif.edu/article_21219_8eab7c9e67c5dc2885e48684f389c846.pdf ER -