Some calibration estimators for finite population mean in two-stage stratified random sampling

Abstract

Some improved estimators are proposed for estimating the population mean in stratified sampling in the presence of auxiliary information. Mean square error (MSE) of the proposed estimators have been derived under large sample approximation. It has been shown that under optimum conditions proposed estimators are better than usual unbiased estimator and Hansen et al. (1946) estimator. Both theoretical and empirical findings are encouraging and support the soundness of the proposed procedure for mean estimation.

Calibration Estimators under Two Auxiliary Variables using Linear and Non-Linear Constraints in Sample Surveys

“…The computation problems become very complicated when multivariate cases are considered in real life cause less concern towards this area. Some recent works on calibration method of estimation include Singh et al (2019), Ozgul et al (2019), Salinas et al (2019), , Sisodia and Singh (2020), Wu and Thompson (2020), among many. .…”