Mixture of vines for dependence modeling: finite mixture and CD-vine approaches with applications

Evkaya, Ömer Ozan
Recently, there has been an increasing interest on the combination of copulas with a finite mixture model. By a finite mixture, a suitable weighted sum of a parametric densities are tied together in a probabilistic manner. The combination of vine copulas incorporated into a finite mixture model is also beneficial to capture hidden structures in a data set. On the other hand, there are limited number of studies about the mixture of vine copulas. In this dissertation, different mixture of vines are proposed for expressing the complex and hidden dependencies in a multivariate data. Firstly, the mixture of vine copulas with different dependence structures are offered to capture the complex association in higher dimension. For this reason, finite mixture of C-vine is studied with different copula pairs. Thereafter, finite mixture of C- and D-vines have been tested with the same copula family. Lastly, as a novel approach, finite number of C-vines are incorporated into a D-vine copula model to derive the association between several variables. The values of cumulative distribution functions for each component having C-vine structure are combined with D-vine by considering the temporal ordering of the components. The performance of the proposed models are tested using simulated and real data sets, then the corresponding results are interpreted in depth.
Citation Formats
Ö. O. Evkaya, “Mixture of vines for dependence modeling: finite mixture and CD-vine approaches with applications,” Ph.D. - Doctoral Program, Middle East Technical University, 2018.