Fitting competing risks data to bivariate Pareto models

Jia-Han Shih, Wei Lee, Li-Hsien Sun and Takeshi Emura

Communications in Statistics - Theory and Methods, 2019, vol. 48, issue 5, 1193-1220

Abstract: 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.

Date: 2019
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DOI: 10.1080/03610926.2018.1425450

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