Fitting competing risks data to bivariate Pareto models. Issue 5 (4th March 2019)

• Record Type: Journal Article
• Authors: Shih, Jia-Han; Lee, Wei; Sun, Li-Hsien; Emura, Takeshi
• Is Part Of: Communications in statistics. Volume 48:Issue 5(2019)
• Page Start: 1193
• Page End: 1220
• Publication Date: 2019-03-04
• Subjects: Bivariate Pareto distribution -- Frank copula -- Kendall's tau -- Newton-Raphson algorithm -- Survival analysis.; Mathematical statistics -- Periodicals; Mathematics; Statistics; 519.2
• DOI: 10.1080/03610926.2018.1425450
• Languages: English
• ISSNs: 0361-0926

Abstract

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.