Estimating Finite Population Mean using Multiple Parameters of an Ancillary Variable

Abstract

This study deals with an improved class of estimators for estimating the unknown finite population mean of the study variable using auxiliary information. It has been developed by using the power transformation in Singh and Yadav (2017) family of estimators. The expression for bias and mean squared error of the proposed estimator is derived under large sample approximation. The conditions have been derived for the suggested class of estimators under which it performs better than the estimators considered in this study. The theoretical results are supported by numerical illustration. Two phase sampling version of the proposed family of estimators is suggested and its properties are also studied. © 2023, Society of Statistics, Computer and Applications. All rights reserved.