Estimation of finite population distribution function in a complex survey sampling
Abdul Haq,
Mohsin Abbas and
Manzoor Khan
Communications in Statistics - Theory and Methods, 2023, vol. 52, issue 8, 2574-2596
Abstract:
In this paper, we develop unbiased estimators of the finite population cumulative distribution function (CDF) using two-stage and three-stage cluster sampling. In addition, the ranked-set sampling scheme is also used in the secondary and tertiary sampling frames for further increasing the precision of the CDF estimators. This work is then extended to develop unbiased CDF estimators based on stratified two-stage and three-stage cluster sampling. Moreover, unbiased estimators of the variances of the proposed CDF estimators are also derived. Real datasets are considered to demonstrate the estimation of the CDF under these complex survey sampling schemes.
Date: 2023
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2021.1955386 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:52:y:2023:i:8:p:2574-2596
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20
DOI: 10.1080/03610926.2021.1955386
Access Statistics for this article
Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe
More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().