Copula models have become increasingly popular for modelling the dependence structure
in multivariate survival data. The two-parameter Archimedean family of Power Variance …

Copulas are bevariate distributions with uniform marginals. They provide a general method
for binding several univariate marginal distributions together to form a multivariate …

In multivariate survival analyses, understanding and quantifying the association between
survival times is of importance. Copulas, such as Archimedean copulas and Gaussian …

We investigate two-stage parametric and two-stage semi-parametric estimation procedures
for the association parameter in copula models for bivariate survival data where censoring in …

Copula is a popular method for modeling the dependence among marginal distributions in
multivariate censored data. As many copula models are available, it is essential to check if …

In this article, we propose a bivariate long-term distribution based on the Farlie-Gumbel-
Morgenstern copula model. The proposed model allows for the presence of censored data …

Copulas and frailty models are important tools to model bivariate survival data. Equivalence
between Archimedean copula models and shared frailty models, eg between the Clayton …

One-sided truncated survival data arise when a pair of time-to-event variables (X, Y) is
observed only when X< Y. Existing methods of analysis rely on the assumption of quasi …

Copula models have become very popular and well studied among the scientific community.
Now, most academic researchers, engineers, modelers, etc, own at least some basic copula …

In recent years, the use of copulas has grown rapidly, especially in survivalanalysis. In this
paper, we introduce a bivariate modied Weibull distribu-tion derived from the Farlie {Gumbel …