Empirical Likelihood Ratio in Terms of Cumulative Hazard Function for Censored Data

Xiao-Rong Pan and Mai Zhou

Journal of Multivariate Analysis, 2002, vol. 80, issue 1, 166-188

Abstract: It has been shown that (with complete data) empirical likelihood ratios can be used to form confidence intervals and test hypotheses about a linear functional of the distribution function just like the parametric case. We study here the empirical likelihood ratios for right censored data and with parameters that are linear functionals of the cumulative hazard function. Martingale techniques make the asymptotic analysis easier, even for random weighting functions. It is shown that the empirical likelihood ratio in this setting can be easily obtained by solving a one parameter monotone equation.

Keywords: weighted; hazard; one; sample; log; rank; test; stochastic; constraint; median (search for similar items in EconPapers)
Date: 2002
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0047-259X(00)91977-8
Full text for ScienceDirect subscribers only

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:eee:jmvana:v:80:y:2002:i:1:p:166-188

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Journal of Multivariate Analysis is currently edited by de Leeuw, J.

More articles in Journal of Multivariate Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().