An Improved Family of Estimators of Finite Population Mean Using Information on an Auxiliary Variable in Sample Surveys

Abstract

In this paper we have suggested a family of estimators of the population mean using auxiliary information in sample surveys. The bias and mean squared error of the proposed class of estimators have been obtained under large sample approximation. We have derived the conditions for the parameters under which the proposed class of estimators has smaller mean squared error than the sample mean, ratio, product, regression estimator and the two parameter ratio-product-ratio estimators envisaged by Chami et al (2012). An empirical study is carried out to demonstrate the performance of the proposed class of estimators over other existing estimators. Mathematics Subject Classification 2000: 62D05

Ratio estimator for double sampling procedure with non-response: An empirical study

“…This was achieved by deriving the expressions for the constant, bias, and mean square errors (MSE) of the proposed estimator. The proposed estimator was compared to ten other existing ratiotype estimators, including Sisodia and Dwivedi (SD) [16], Upadhyaya and Singh (US) [17], Singh and Tailor (ST) [18], Singh et al (SET) [19], Yan and Tain (YT) [20], Subramani and Krumarpandiyan (SK) [21], Hazara (H) [22], Jerajuddin and Kishun (JK) [23], Ijaz et al (IET) [24], and Suleiman and Adewara (SA) [25]. Three distinct sources of five natural populations were used by the present study to assess the estimators' performance.…”