Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/25723
Title: Empirical likelihood confidence regions for one- or two- samples with doubly censored data
Authors: Shen, J
Yuen, KC
Liu, C 
Keywords: Chi-square convergence
Confidence region
Doubly censored data
EM algorithm
Empirical likelihood ratio
Moment constraint
Issue Date: Jan-2016
Publisher: Elsevier
Source: Computational statistics and data analysis, Jan. 2016, v. 93, p. 285-293 How to cite?
Journal: Computational Statistics and Data Analysis 
Abstract: The purpose is to propose a new EM algorithm for doubly censored data subject to nonparametric moment constraints. Empirical likelihood confidence regions are constructed for one- or two- samples of doubly censored data. It is shown that the corresponding empirical likelihood ratio converges to a standard chi-square random variable. Simulations are carried out to assess the finite-sample performance of the proposed method. For illustration purpose, the proposed method is applied to a real data set with two samples.
URI: http://hdl.handle.net/10397/25723
ISSN: 0167-9473
DOI: 10.1016/j.csda.2015.01.010
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