A New Regression Type Estimator and Its Application in Survey Sampling

• 作者: K. Fatema M. Murad Hossain M. Sultana M. Zahid Hasan Md. Ali Hossain
• 来源期刊: 统计学期刊(英文)
• 学科: 数学
• 关键词: Auxiliary Information BIAS EFFICIENCY Mean Square Error Product and Ratio Estimator
• 年，卷（期）: 2020,（6）
• 页码范围: 1010-1019
• 页数: 10页
• 分类号: O17

摘要

In the present time, a large number of modified estimators have been proposed by authors to obtain efficiency. In this study, we suggested an alternative regression type estimator for estimating finite population mean</span><span style="font-family:Verdana;">s</span><span style="font-family:Verdana;"> when there is either </span><span style="font-family:Verdana;">a </span><span style="font-family:Verdana;">positive or negative correlation between study variables and auxiliary variables. We obtained bias and mean square error equation of the proposed estimator ignoring the first</span><span style="font-family:Verdana;">-</span><span style="font-family:Verdana;">order approximation and found the theoretical conditions that make proposed estimator more efficient than simple random sampling mean estimator, product estimator and ratio estimator. In addition, these conditions are supported by a numerical example and it has been concluded that the proposed estimator performed better comparing with the usual simple random sampling mean estimator, ratio estimator and product estimator.