Liouville Copulas

Not merged yet !

Liouville copulas are coming in this PR : https://github.com/lrnv/Copulas.jl/pull/83, but this is not merged yet.

Archimedean copulas have been widely used in the literature due to their nice decomposition properties and easy parametrization. The interested reader can refer to the extensive literature [2430, 3033] on Archimedean copulas, their nesting extensions and most importantly their estimation.

One major drawback of the Archimedean family is that these copulas have exchangeable marginals (i.e., $C(\bm u) = C(\mathrm{p}(\bm u))$ for any permutation $p(\bm u)$ of $u_1,...,u_d$): the dependence structure is symmetric, which might not be a wanted property. However, from the Radial-simplex expression, we can easily extrapolate a little and take for $\bm S$ a non-uniform distribution on the simplex.

Liouville's copulas share many properties with Archimedean copulas, but are not exchangeable anymore. This is an easy way to produce non-exchangeable dependence structures. See [15] for a practical use of this property.

Note that Dirichlet distributions are constructed as $\bm S = \frac{\bm G}{\langle \bm 1, \bm G\rangle}$, where $\bm G$ is a vector of independent Gamma distributions with unit scale (and potentially different shapes: taking all shapes equal yields the Archimedean case).

[15]
M.-P. Côté and C. Genest. Dependence in a Background Risk Model. Journal of Multivariate Analysis 172, 28–46 (2019).
[24]
M. Hofert. Sampling Nested Archimedean Copulas with Applications to CDO Pricing. Ph.D. Thesis, Universität Ulm (2010).
[25]
M. Hofert and D. Pham. Densities of Nested Archimedean Copulas. Journal of Multivariate Analysis 118, 37–52 (2013).
[26]
A. J. McNeil and J. Nešlehová. From Archimedean to Liouville Copulas. Journal of Multivariate Analysis 101, 1772–1790 (2010).
[27]
H. Cossette, S.-P. Gadoury, E. Marceau and I. Mtalai. Hierarchical Archimedean Copulas through Multivariate Compound Distributions. Insurance: Mathematics and Economics 76, 1–13 (2017).
[28]
H. Cossette, E. Marceau, I. Mtalai and D. Veilleux. Dependent Risk Models with Archimedean Copulas: A Computational Strategy Based on Common Mixtures and Applications. Insurance: Mathematics and Economics 78, 53–71 (2018).
[29]
C. Genest, J. Nešlehová and J. Ziegel. Inference in Multivariate Archimedean Copula Models. TEST 20, 223–256 (2011).
[30]
E. Di Bernardino and D. Rulliere. On Certain Transformations of Archimedean Copulas: Application to the Non-Parametric Estimation of Their Generators. Dependence Modeling 1, 1–36 (2013).
[31]
E. Di Bernardino and D. Rullière. On an Asymmetric Extension of Multivariate Archimedean Copulas Based on Quadratic Form. Dependence Modeling 4 (2016).
[32]
K. Cooray. Strictly Archimedean Copulas with Complete Association for Multivariate Dependence Based on the Clayton Family. Dependence Modeling 6, 1–18 (2018).
[33]
J. Spreeuw. Archimedean Copulas Derived from Utility Functions. Insurance: Mathematics and Economics 59, 235–242 (2014).