A Family of Estimators of Population Mean Using Auxiliary Information in Stratified Sampling

Abstract

Abstract This article suggests a family of estimators of population mean using auxiliary information in stratified sampling. The bias and mean-squared error of the suggested family of estimators are derived under large sample approximation. Asymptotic optimum estimator (AOE) in the class of estimators is investigated with its mean-squared error formula. It is identified that the usual unbiased estimator , traditional combined ratio estimator , traditional combined regression estimator , Kadilar and Cingi (Citation2005) estimator , and Shabbir and Gupta (Citation2006) estimator are particular members of a suggested family of estimators. The new expressions of bias and a mean-square error of Kadilar and Cingi (Citation2005) estimator and a new expression of a mean-square error of Shabbir and Gupta (Citation2006) estimator have been derived. Both theoretical and empirical findings are encouraging and support the soundness of the present study. Keywords: Auxiliary variateBiasMean-squared errorStratified samplingStudy variateMathematics Subject Classification: 62D05 Acknowledgments Authors are thankful to the editor-in-chief Prof. N. Balakrishnan and the referee for their valuable suggestions regarding improvements to this article.