Variance estimation based on L-moments and auxiliary information
Usman Shahzad, Ishfaq Ahmad, Ibrahim M. Almanjahie, Nursel Koyuncu, Muhammad Hanif
Abstract
The presence of extreme values in a data set reduces the efficiency of variance estimators. L-moments are based on the ordered form of a random variable to estimate the variance of the population. The two variance estimators are used for calibration to a stratified random sampling design and relying on an auxiliary variable. The proposed estimators use the properties of L-moments, such as the L-mean, also called L-location, the L-standard deviation, also called L-scaling, and the L-coefficient of variation, which is a measure of variation. The use of these properties allows for providing better estimators. A simulation proves the better efficiency of these estimators.