Improved Ratio Estimators Using Some Robust Measures

Estimation of population mean is of prime concern in many studies  and ratio estimators are popular choices for it. It is a common practice to use conventional measures of location to develop ratio estimators  using information on auxiliary variables. In this article, we propose a class of ratio estimators for a finite population mean using information  on two auxiliary variables with the help of some non-conventional location measures. We have incorporated tri-mean, Hodges-Lehmann,  mid-range and decile mean of the two auxiliary variables to serve the purpose. The properties associated with the proposed class of ratio  estimators are evaluated using mean square error. We have presented efficiency comparisons of the proposed class of ratio estimators with  other existing estimators under the optimal conditions. An empirical study is also included for illustration and verication purposes. From  theoretical and empirical study, We observed that the proposed estimators perform better as compared to the usual ratio and the existing estimators consider in this study.