Estimation of Mean in Double Sampling Using Exponential Technique on Multi-auxiliary Variates

Abstract

This paper presents exponential-type ratio and product estimators for a finite population mean in double sampling using information on several auxiliary variates. The proposed estimators can be viewed as a generalization over the estimators suggested by Singh and Vishwakarma (Austrian J Stat 36(3):217–225, 2007). The expressions for biases and mean square errors (MSEs) of the proposed estimators have been derived to the first degree of approximation. In addition, the expressions for minimum attainable MSEs are also investigated using the criterion for optimality of the weights. An empirical study is carried out in the support of the present study. Both theoretical and empirical findings are encouraging and support the soundness that the proposed procedures for mean estimation perform better than the usual unbiased estimators and other well-known estimators under some realistic conditions.