An effective computational and simulation study for population mean estimation on current occasion

In general, successive sampling is the procedure to study the effect of the change in a characteristic on different occasions. We have suggested a new effective approach to analyze the estimate of population mean on current occasion under successive sampling. The properties of the proposed novel class under the suggested approach are derived by using optimum replacement policy. The superiority of the class is demonstrated through theoretical, numerical and simulation study. The simulation based mean square errors are computed under optimum unmatched proportion of their respective class of estimators. The suggested approach of estimation is fruitful for survey practitioners to handle large as well as small populations.