missing data;
ratio estimator;
ranked set sampling;
gain in accuracy;
IMPUTATION;
INFERENCE;
D O I:
10.1002/env.2286
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
The existence of missing observations (MO) is commonly solved by using imputation methods. There are ratio-based methods for estimating the population mean, while using simple random sampling (SRS), when MO are present. Considering the existence of MO and using of ranked set sampling, we develop a study of the estimation of a population mean using ratio-based methods. The mean square errors, bias, and gain in accuracy formulas of the suggested estimators are derived. The suggested estimators are compared with their SRS counterpart both theoretically and numerically. Copyright (c) 2014 John Wiley & Sons, Ltd.
机构:
Department of Mathematics and Statistics, Manipal University Jaipur, Jaipur, 303007, RajasthanDepartment of Mathematics and Statistics, Manipal University Jaipur, Jaipur, 303007, Rajasthan
Saini M.
Kumar A.
论文数: 0引用数: 0
h-index: 0
机构:
Department of Mathematics and Statistics, Manipal University Jaipur, Jaipur, 303007, RajasthanDepartment of Mathematics and Statistics, Manipal University Jaipur, Jaipur, 303007, Rajasthan