摘要：One of the most significant topics in statistics is the issue of variance estimation. In the research literature, various variance estimators are con-structed based on traditional moments that are par-ticularly affected by the presence of extreme values. Therefore, the focus of this paper is on the adoption ofL-Moments features to propose some new calibra-tion estimators for a variance with some suitable cal-ibration constraints under stratified random sam-pling. The empirical efficiency of proposed estima-tors is calculated through simulation based on Covid-19 pandemic data for the period January 22, 2020, up to August 23,2020.The results indicate that the proposed estimators are superior and highly efficient compared to the existing traditional estima-tor when the data includes extreme values.
关键词：Variance estimation;L-Moments;Calibration;Stratified random sampling
