THE IDENTIFIABILITY OF COPULA MODELS FOR DEPENDENT COMPETING RISKS DATA WITH EXPONENTIALLY DISTRIBUTED MARGINS

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Abstract

We prove the identifiability property of Archimedean copula models for dependent competing risks data when at least one of the failure times is exponentially distributed. With this property, it becomes possible to quantify the dependence between competing events based on exponentially distributed dependent censored data. We demonstrate our estimation procedure using simulation studies and in an application to survival data.

Original languageEnglish (US)
Pages (from-to)983-1001
Number of pages19
JournalStatistica Sinica
Volume33
Issue number2
DOIs
StatePublished - Apr 2023

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Keywords

  • Archimedean copula models
  • copula graphic estimator
  • identifiability of competing risks data

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