Ameliorate estimation of mean using skewness and kurtosis of auxiliary character

Abstract

In this research article, improved regressed exponential estimators for estimating the finite population mean have been suggested using the coefficient of skewness and kurtosis of an auxiliary character. Other known parameters and constants like median, quartile deviation, Gini’s mean difference, Downton’s method and probability weighted moments of auxiliary character are utilized to improve the efficiency of the suggested estimators. The bias (Bs) and mean square error (Mse) of proposed estimators are obtained up to the first degree of approximation under large sample approach. The values of unknown constants involved in proposed estimators are obtained to minimize the mean square errors. Theoretical and empirical discussions reveal that the proposed estimators are more efficient than the traditional and all the recent relevant estimators.