Empirical likelihood with twice censored data

Mohamed Boukeloua

Communications in Statistics - Theory and Methods, 2025, vol. 54, issue 18, 6081-6115

Abstract: We consider the problem of the construction of confidence intervals for some functionals of a distribution of interest. These functionals include the moments of the distribution, the survival function, and the mean residual life, among others. The empirical likelihood method has been extensively used to construct such confidence intervals in the cases of complete and right censored data. In this article, we deal with the case of twice censored data, where right and left censoring are simultaneously involved. In this context, we propose an empirical likelihood ratio function which we use to construct confidence intervals for some functionals of the distribution of interest. The advantage of our method lies in the fact that our proposed empirical likelihood ratio function converges to a chi-square distribution without being multiplied by any scale parameters, which is the case for many empirical likelihood versions that exist in the setting of censored data. Therefore, we use our empirical likelihood ratio function to construct the desired confidence intervals without involving any further estimation of the scale parameters. This allows to improve the coverage accuracy of our confidence intervals. Finally, we show the performances of our method through a simulation study and a real data application.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2025.2450027 (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:54:y:2025:i:18:p:6081-6115

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2025.2450027

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 ().