Likelihood-based inference for bivariate latent failure time models with competing risks under the generalized FGM copula

Computational Statistics volume 33, pages1293–1323(2018)Cite this article

Abstract

Many existing latent failure time models for competing risks do not provide closed form expressions of sub-distribution functions. This paper suggests a generalized FGM copula models with the Burr III failure time distribution such that the sub-distribution functions have closed form expressions. Under the suggested model, we develop a likelihood-based inference method along with its computational tools and asymptotic theory. Based on the expressions of the sub-distribution functions, we propose goodness-of-fit tests. Simulations are conducted to examine the performance of the proposed methods. A real data from the reliability analysis of the radio transmitter-receivers are analyzed to illustrate the proposed methods. The computational programs are made available in the R package GFGM.copula.

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Acknowledgements

The authors thank the co-editor and two anonymous reviewers for their helpful comments that greatly improved the presentation of the paper. This work is supported by the research grants funded by the government of Taiwan (MOST 103-2118-M-008-MY2; MOST 105-2118-M-008-003-MY2).

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  1. Graduate Institute of Statistics, National Central University, No. 300, Zhongda Rd., Zhongli District, Taoyuan City, 32001, Taiwan

    Jia-Han Shih & Takeshi Emura

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  1. Jia-Han Shih
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  2. Takeshi Emura
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Correspondence to Takeshi Emura.

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Shih, J., Emura, T. Likelihood-based inference for bivariate latent failure time models with competing risks under the generalized FGM copula. Comput Stat 33, 1293–1323 (2018). https://doi.org/10.1007/s00180-018-0804-0

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Keywords

  • Bivariate survival analysis
  • Burr III distribution
  • Copula
  • Parametric bootstrap
  • Reliability