Ratio-type estimators for improving mean estimation using Poisson regression method
Haydar Koç
Communications in Statistics - Theory and Methods, 2021, vol. 50, issue 20, 4685-4691
Abstract:
Poisson regression model is the most common method used to model count response in many studies. This paper proposes a new ratio-type estimators based on Poisson regression in simple random sampling. The mean square error (MSE) equation of these estimators is obtained in this study. Theoretically, the MSE of the proposed estimators and the MSE of the traditional ratio estimators are compared. As a result of these comparisons, it has shown that the suggested estimator is more efficient than the traditional estimators. In addition, the results of the application part supported the theoretical findings of the study.
Date: 2021
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2020.1777307 (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:50:y:2021:i:20:p:4685-4691
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20
DOI: 10.1080/03610926.2020.1777307
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 ().