Memory-type ratio and product estimators for population variance using exponentially weighted moving averages for time-scaled surveys
Muhammad Nouman Qureshi, Muhammad Umair Tariq, Muhammad Hanif
Abstract
In this study, we have proposed memory-type ratio and product estimators for the estimation of population variance based on exponentially weighted moving averages (EWMA) statistic. The EWMA statistic simultaneously utilizes the current and previous information in time-scaled surveys. The equations of approximate mean square errors are established for proposed memory-type ratio and product estimators. The performance of the proposed estimators is evaluated mathematically by deriving the conditions in which memory-type ratio and product estimators are better than the conventional ratio and product estimators. The results of simulation study and real data application revealed that the use of previous sampled information excels the efficiency of the proposed estimators for time-scaled surveys.