Some new classes of estimators under linear systematic sampling in absence and presence of non-response. Issue 6 (18th August 2019)

• Record Type: Journal Article
• Authors: Shahzad, Usman; Hanif, Muhammad; Koyuncu, Nursel
• Is Part Of: Journal of statistics & management systems. Volume 22:Issue 6(2019)
• Page Start: 1067
• Page End: 1091
• Publication Date: 2019-08-18
• Subjects: 62D05; Auxiliary information -- Systematic random sampling -- Bias -- Percentage relative efficiency; Statistics -- Periodicals; Mathematical models -- Periodicals; Mathematical models; Statistics; Periodicals; 519.5
• DOI: 10.1080/09720510.2018.1564582
• Languages: English
• ISSNs: 0972-0510

Abstract

Abstract: Systematic sampling is a statistical method involving the selection of elements from an ordered sampling frame. Singh and Solanki (2012) and Singh et al. (2012) introduced some estimators for estimating the population mean using supplementary information in systematic sampling. In this article we propose some new and improved classes of estimators by adapting Koyuncu (2012) and Swain (2014) estimators for population mean under systematic sampling scheme alongside the non-response issue. The properties of the proposed classes such as biases and mean square errors are derived theoretically. A numerical study is performed to see the superiority of our proposed estimators.