Likelihood-based inference for a frailty-copula model based on competing risks failure time data
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
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Detail(s)
Original language | English |
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Pages (from-to) | 1622-1638 |
Journal / Publication | Quality and Reliability Engineering International |
Volume | 36 |
Issue number | 5 |
Online published | 11 May 2020 |
Publication status | Published - Jul 2020 |
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Abstract
A competing risks phenomenon arises in industrial life tests, where multiple types of failure determine the working duration of a unit. To model dependence among marginal failure times, copula models and frailty models have been developed for competing risks failure time data. In this paper, we propose a frailty-copula model, which is a hybrid model including both a frailty term (for heterogeneity among units) and a copula function (for dependence between failure times). We focus on models that are useful to investigate the reliability of marginal failure times that are Weibull distributed. Furthermore, we develop likelihood-based inference methods based on competing risks data, including accelerated failure time models. We also develop a model-diagnostic procedure to assess the adequacy of the proposed model to a given dataset. Simulations are conducted to demonstrate the operational performance of the proposed methods, and a real dataset is analyzed for illustration. We make an R package “gammaGumbel” such that users can apply the suggested statistical methods to their data.
Research Area(s)
- competing risk, copula, frailty, reliability, Weibull distribution
Citation Format(s)
Likelihood-based inference for a frailty-copula model based on competing risks failure time data. / Wang, Yin-Chen; Emura, Takeshi ; Fan, Tsai-Hung; Lo, Simon M.S.; Wilke, Ralf Andreas.
In: Quality and Reliability Engineering International, Vol. 36, No. 5, 07.2020, p. 1622-1638.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review