Speaker
O. Ozan Evkaya
(Atılım University)
Description
Recently, there has been an increasing interest on the combination of copulas with a finite mixture model. Such a framework is useful to reveal the hidden dependence patterns observed for random variables flexibly in terms of statistical modeling. The combination of vine copulas incorporated into a finite mixture model is also beneficial for capturing hidden structures on a multivariate data set. In this respect, the main goal of this study is extending the study of Kim et al. (2013) with different scenarios. For this reason, finite mixture of C-vine is proposed for multivariate data with different dependence structures. The performance of the proposed model has been tested by different simulated data set including various tail dependence properties.
Primary author
O. Ozan Evkaya
(Atılım University)
Co-authors
A. Sevtap Kestel
(Middle East Technical University)
Ceylan Yozgatlıgil
(Middle East Technical University)
