Generalized Class of Variance Estimators under Two-Phase Sampling for Partial Information Case

Abstract

This paper considers a class of generalized estimators for estimating the unknown population variance using two auxiliary variables when mean of one auxiliary variable may not be available. The expressions for bias and mean square error of the proposed estimators are obtained up to the first order of approximation. Conditions for which the proposed generalized estimator is more efficient than the existing estimators have been derived. Both empirical and simulation studies have also been carried out to analyze the efficiency of the proposed estimators with some existing estimators.