Fitting competing risks data to bivariate Pareto models

  • Wei Lee (貢獻者)
  • Li-Hsien Sun (貢獻者)
  • Takeshi Emura (貢獻者)
  • Jia Han Shih (貢獻者)



This paper revisits two bivariate Pareto models for fitting competing risks data. The first model is the Frank copula model, and the second one is a bivariate Pareto model introduced by Sankaran and Nair (1993). We discuss the identifiability issues of these models and develop the maximum likelihood estimation procedures including their computational algorithms and model-diagnostic procedures. Simulations are conducted to examine the performance of the maximum likelihood estimation. Real data are analyzed for illustration.
可用日期4 3月 2019
發行者figshare Academic Research System