Multivariate statistical simulation
Multivariate statistical simulation
A goodness of fit test for copulas based on Rosenblatt's transformation
Computational Statistics & Data Analysis
Bivariate Student t distributions with variable marginal degrees of freedom and independence
Journal of Multivariate Analysis
On the choice of the smoothing parameter for the BHEP goodness-of-fit test
Computational Statistics & Data Analysis
Meta densities and the shape of their sample clouds
Journal of Multivariate Analysis
Efficient maximum likelihood estimation of copula based meta t-distributions
Computational Statistics & Data Analysis
A copula-based model of speculative price dynamics in discrete time
Journal of Multivariate Analysis
Vine copulas with asymmetric tail dependence and applications to financial return data
Computational Statistics & Data Analysis
Selecting and estimating regular vine copulae and application to financial returns
Computational Statistics & Data Analysis
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Based on an analysis of copulas of elliptically contoured distributions, joint densities of continuous variables with given strictly increasing marginal distributions are constructed. A method utilized for this procedure is to embed the spherical distribution quantile transformation of each variable into an elliptically contoured distribution. The new class of distributions is then called meta-elliptical distributions. The corresponding analytic forms of the density, conditional distribution functions, and dependence properties are derived. This new class of distributions has the same Kendall's rank correlation coefficient as meta-Gaussian distributions. As an extension of elliptically contoured distributions, some new classes of distributions are also obtained.