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

Jia-Han Shih () and Takeshi Emura ()
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Jia-Han Shih: National Central University
Takeshi Emura: National Central University

Computational Statistics, 2018, vol. 33, issue 3, No 10, 1293-1323

Abstract: 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.

Keywords: Bivariate survival analysis; Burr III distribution; Copula; Parametric bootstrap; Reliability (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (8)

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DOI: 10.1007/s00180-018-0804-0

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