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Inference for constant-stress Weibull competing risks model under generalized progressive hybrid censoring

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  • Wang, Liang
  • Tripathi, Yogesh Mani
  • Lodhi, Chandrakant
  • Zuo, Xuanjia

Abstract

In this paper, accelerated life test is considered when the latent failure times follow Weibull competing risks models. When both scale and shape parameters are nonconstant and affected by operating stress, inference is discussed for a constant-stress model under a generalized progressive hybrid censoring. Maximum likelihood estimates together with existence and uniqueness are established, and the approximate confidence intervals for unknown parameters are proposed based on the asymptotic theory. Further, when the distributions of failure causes have common shape or scale parameters, associated point and interval estimates are also proposed. In addition, to compare the equivalence of the parameters of different Weibull competing risks, likelihood ratio tests for interested hypotheses are presented for complementary. Finally, extensive numerical studies and a real-life example are provided for illustrations.

Suggested Citation

  • Wang, Liang & Tripathi, Yogesh Mani & Lodhi, Chandrakant & Zuo, Xuanjia, 2022. "Inference for constant-stress Weibull competing risks model under generalized progressive hybrid censoring," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 192(C), pages 70-83.
    • Handle: RePEc:eee:matcom:v:192:y:2022:i:c:p:70-83
    DOI: 10.1016/j.matcom.2021.08.017
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    References listed on IDEAS

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