Pair-copula constructions
A copula is a multivariate distribution with standard uniform marginal distributions. While the literature on copulas is substantial, most of the research is still
limited to the bivariate case. However, recently hierarchical copula-based structures have been proposed as an alternative to the standard copula methodology.
One of the most promising of these structures is the pair-copula construction (PCC). The PCCs were originally proposed by Harry Joe in 1996. In 2002, Bedford and Cooke
organised these constructions by means of graphical models denoted regular vines and the PCCs/vines were further explored by Kurowicka and Cooke during the years
2002-2009. After being set in an inferential context by Aas et. al. in 2009, the interest in the PCCs has grown steadily and these constructions are finding successful
applications in various fields. At this web page we try to keep updated information on papers, software and conferences related to pair-copula constructions.
Kjersti Aas (Norwegian Computing Center)
Publications
Joe, H., "Families of m-variate distributions with given margins and m(m-1)/2 bivariate dependence parameters". In Distributions with Fixed Marginals and
Related Topics, eds. L. Rueschendorf, B. Schweizer and M.D. Taylor, IMS Lecture Notes-Monograph Series. Hayward, CA, pp. 120-141, 1996.
Bedford, T. and Cooke, R., "Vines - a new graphical model for dependent random variables", Annals of Statistics, 30, 1031-1068, 2002.
Aas, K., Czado, C., Frigessi, A. and Bakken, H.: "Pair-copula constructions of multiple dependence", Insurance: Mathematics and Economics, Vol. 44, No. 2, 2009.
List of papers citing the Aas et. al. (2009) paper
Books
Dependence Modeling: Vine Copula Handbook
Uncertainty Analysis with High Dimensional
Dependence Modelling
Software
Copulaedas (R)
CDVine (R)
Vines (R)
Dynamic Copula Toolbox 3.0 (MATLAB)
Conferences
1st Vine Copula Workshop , Delft, November 2007
2nd Vine Copula Workshop , Delft, December 2008
3rd Vine Copula Workshop , Oslo, December 2009
4th Vine Copula Workshop , Munich, May 2011
Applications
PCCs have e.g. been applied in the following areas:
Finance
Insurance
Genetics
Health
Hydrology
Longitudinal data
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