The Ratio-type Estimators of Variance with Minimum Average Square Error

The ratio-type estimators have been introduced for estimating the mean and total population, but in recent years based on the ratio methods several estimators for population variance have been proposed. In this paper two families of estimators have been suggested and their approximation mean square error (MSE) have been developed. In addition, the efficiency of these variance estimators are compared. We also show that their performance is better than traditional ratio estimator. Finally, a computational approach to find the optimum values of parameters is introduced and by using rice fields data of Amol county of Iran, an empirical study is carried out to show that this approach is the best. In this manner, since the values of estimators MSE are approximated, to obtain the approximately unbiased estimator with minimum variance, average square error (ASE) is used.