A generalized family of estimators for estimating finite population mean in circular systematic sampling (CSS)

Abstract

This paper aims to discuss the problem of estimating the population mean of the study variable y using information on an auxiliary variable x in circular systematic sampling (CSS) scheme along with the non-response problem. We have suggested a generalized family of estimators for population mean of y based on auxiliary variable x. We have derived the expressions for bias and mean squared error of the proposed family of estimators upto first order of approximation. Optimum conditions are obtained in which the suggested family of estimators has the least mean squared error. It has been shown that the proposed family of estimators is better than usual unbiased estimator, ratio estimator and the regression estimator. An empirical study is provided to show that the suggested family of estimators is better than the ratio and regression estimators.