Optimal classes of estimators for population mean using higher order moments

This paper considers some optimal classes of difference and ratio type estimators for the estimation of population mean using higher order moments viz variance of auxiliary variable with the aim of improvement over its entrants existing till date. The bias and mean square error of the considered estimators are derived using Taylor series method up to the first order of approximation. The theoretical results have been determined and appraised with a computational study using real and artificially generated data sets. The computational results are turned out to be rather advance providing better improvement over the contemporary estimators.