Robust ratio‐type estimators for finite population mean in simple random sampling: A simulation study. (10th August 2022)

• Record Type: Journal Article
• Authors: Zaman, Tolga; Bulut, Hasan; Yadav, Subhash Kumar
• Is Part Of: Concurrency and computation. Volume 34:Number 25(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-08-10
• Subjects: efficiency -- outliers -- ratio‐type estimators -- robust regression techniques; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.7273
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: In this study, ratio estimators are proposed by utilizing some robust techniques to get the maximum benefit of the auxiliary variable for the estimation of the population mean in simple random sampling. The expressions for mean squared error are derived for the first degree of approximation. Theoretical comparisons demonstrate that the suggested estimators having robust regression estimates perform better than the existing estimators under certain conditions. Theoretical findings are supported with the aid of the original dataset in an application. In addition, a simulation study is also conducted to evaluate the performance of the suggested estimators.