Mixture of D-vine copulas for modeling dependence

  title={Mixture of D-vine copulas for modeling dependence},
  author={Daeyoung Kim and Jong-Min Kim and Shu-Min Liao and Yoon-Sung Jung},
  journal={Computational Statistics & Data Analysis},
The identification of an appropriate multivariate copula for capturing the dependence structure in multivariate data is not straightforward. The reason is because standard multivariate copulas (such as the multivariate Gaussian, Student-t, and exchangeable Archimedean copulas) lack flexibility to model dependence and have other limitations, such as parameter restrictions. To overcome these problems, vine copulas have been developed and applied to many applications. In order to reveal and fully… CONTINUE READING
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Publications referenced by this paper.
Showing 1-10 of 41 references

Goodness-of-fit procedures for copulamodels based on the probability integral transform

  • C. 543–552. Genest, Quessy, J.-F, B. Rémillard
  • Scandinavian Journal of Statistics
  • 2006
Highly Influential
4 Excerpts

Distribution — free continuous bayesian belief nets

  • D. Kurowicka, R. M. Cooke
  • in: Fourth International Conference on…
  • 2004
Highly Influential
5 Excerpts

Statistical applications of the multivariate skew normal distribution

  • A. Azzalini, A. Capitanio
  • Information Theory. Akademiai Kiado,
  • 1999
Highly Influential
3 Excerpts

Model selection and Akaikes information criterion (AIC): the general theory and its analytical extensions

  • H. Bozdogan
  • Psychometrika
  • 1987
Highly Influential
3 Excerpts

Development Core Team, 2012. R: A Language and Environment for Statistical Computing

  • R Foundation for Statistical Computing,
  • 2012

Truncated and simplified regular vines in high dimensions with application to financial data

  • E. C. Brechmann, U. Schepsmeier
  • Canadian Journal of Statistics
  • 2012

Modeling dependence with C- and D-vine copulas: The R-package CDVine. R vignette of the R-package CDVine

  • E. C. Brechmann, U. Schepsmeier
  • 2011
1 Excerpt

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