AN EFFICIENT FAMILY OF RATIO-CUM-PRODUCT ESTIMATORS FOR FINITE POPULATION MEAN IN SAMPLE SURVEYS

Authors : Housila P SİNGH, Anita YADAV

Pages : 29-45

View : 25 | Download : 11

Publication Date : 2018-01-01

Article Type : Research Paper

Abstract :This paper considers the problem of estimating the finite population mean $\bar{Y}$  of the study variable using information on two auxiliary variables $insert ignore into journalissuearticles values(x,z);$ . A family of ratio-cum-product estimators for population mean $\bar{Y}$  has been suggested. It has been shown that the usual unbiased estimator $\bar{y}$ , ratio estimator, product estimator, dual to ratio estimator and dual to product estimator due to Srivenkatramana insert ignore into journalissuearticles values(1980); and Bandyopadhyaya insert ignore into journalissuearticles values(1980);, Singh et al`s insert ignore into journalissuearticles values(2005, 2011); estimator, Tailor et al`s insert ignore into journalissuearticles values(2012); estimator, Vishwakarma et al`s insert ignore into journalissuearticles values(2014); estimator and  Vishwakarma and Kumar insert ignore into journalissuearticles values(2015); estimator are members of the suggested family of estimators. In addition to these estimators, various unknown estimators are shown to be the member of the suggested family of estimators. The bias and mean squared error of the proposed family are obtained under large sample approximation. Efficiency comparisons are made to demonstrate the performance of the suggested family over other existing estimators. An empirical study is carried out in support of the present study.
Keywords : Auxiliary variables, Study variable, Ratio cum Product method of estimation, Bias, Mean Squared Error