Open AccessENHANCING EFFICIENCY OF RATIO ESTIMATOR OF POPULATION MEDIAN BY CALIBRATION TECHNIQUES
Author(s) -
Matthew Joshua
Publication year - 2020
Publication title -
international journal of engineering, sciences and research technology
Language(s) - English
Resource type - Journals
ISSN - 2277-9655
DOI - 10.29121/ijesrt.v9.i8.2020.2
Subject(s) - estimator , statistics , mathematics , ratio estimator , stratified sampling , calibration , sampling (signal processing) , mean squared error , minimum variance unbiased estimator , population , efficient estimator , bias of an estimator , sample size determination , cauchy distribution , computer science , demography , filter (signal processing) , sociology , computer vision
The use of calibration estimation techniques in survey sampling have been found to improve the precision of estimators. This paper adopts the calibration approach with the assumption that the population median of the auxiliary variable is known to obtain a more efficient ratio-type estimator in estimating population median in stratified sampling. Conditions necessary for efficiency comparison have been obtained which show that the proposed estimator will always perform better than the existing asymptotically unbiased separate estimators in stratified random sampling. Numerical evaluations have been carried out through simulation and real-life data to compliment the theoretical claims. Results from the simulation study carried out under three distributional assumptions, namely the chi square, lognormal and Cauchy distributions with different sample settings showed that the new estimator provided better estimate of the median with greater gain in efficiency. In addition, result from the real-life data further supports the superiority of the proposed estimator over the existing ones considered in this study.