Some ratio type predictive estimators for estimation of the average water level of a river using season as an auxiliary attribute

The study aims to estimate the average water level of a river using an auxiliary attribute under a predictive approach. As the average water level varies in different seasons, the study considers the average water level as a study variable and the season an auxiliary attribute. A real data set of the water level of the Jhelum River at Mangla is obtained. As we found a positive correlation between the average water level and the season, we have suggested some ratio-type predictive estimators for estimating the average water level. The mean square errors (MSE) and bias of the suggested estimators are obtained using the MSE and bias of the corresponding conventional (design-based) estimators. The performance of the proposed predictive estimators, relative to their related existing estimators, has been studied, and improved performance has been established.