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Empirical likelihood confidence regions for one- or two- samples with doubly censored data

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  • Shen, Junshan
  • Yuen, Kam Chuen
  • Liu, Chunling

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.

Suggested Citation

  • Shen, Junshan & Yuen, Kam Chuen & Liu, Chunling, 2016. "Empirical likelihood confidence regions for one- or two- samples with doubly censored data," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 285-293.
    • Handle: RePEc:eee:csdana:v:93:y:2016:i:c:p:285-293
    DOI: 10.1016/j.csda.2015.01.010
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    References listed on IDEAS

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