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Empirical likelihood confidence regions for one- or two- samples with doubly censored data
- Shen, Junshan, Yuen, Kam Chuen, Liu, Chunling
- Computational statistics & data analysis 2016 v.93 pp. 285-293
- algorithms, data collection
- 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.