Sentence examples for multivariate copulas to from inspiring English sources

Efficiency estimates are computed using multivariate copulas to control for time (trend) and individual (DMU) effects.

Detailed proofs follow in the Appendices 1 and 2. In response to the difficulties encountered with the multivariate normal copula, the pair-copula construction of multivariate copulas has become more and more popular as can be seen from the recent review by Czado (2010).

In practical applications, high-dimensional dependence requires feasible multivariate Copulas and even flexible combinations of different Copula functions.

Comparisons of the environmental contours using C-vines with those obtained from standard multivariate copulas are also discussed.

Moreover, some researches could be conducted using other multivariate copulas and compare the results with the present work.

Three methods of creating multivariate copulas were applied and the results were compared using (1) Kendall's measure; (2) empirical multivariate distributions; and (3) simulations.

The parametric estimation of multivariate copulas is a method that could be applied [20].

Pair-Copula theory maintains the merits of Copula theory, and further provides a flexible and intuitive way to build the multivariate Copula using bivariate Copula blocks.

In this study, we decide to employ a multivariate copula, which is more applicable in practice; the traditional candidate for modeling dependence is Gaussian copula (for application of this copula in a real bank see Aue and Kalkbrener (2006)).

A multivariate copula, which is established based on bivariate copulas and conditional probability distributions, is employed to describe temporal dependences (single site) and spatial dependences (between sites).

Both of these models outperform other standard multivariate copula in modeling multivariate flood data that exhibiting complex patterns of dependence, particularly in the tails.