Sentence examples for multivariate copula in from inspiring English sources
Both of these models outperform other standard multivariate copula in modeling multivariate flood data that exhibiting complex patterns of dependence, particularly in the tails.
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)).
In this paper, a multivariate copula based modeling methodology for dynamic reliability modeling of weighted-k-out-of-n systems is applied.
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).
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 practical applications, high-dimensional dependence requires feasible multivariate Copulas and even flexible combinations of different Copula functions.
Efficiency estimates are computed using multivariate copulas to control for time (trend) and individual (DMU) effects.
The aim of the current study is to emphasize the importance of nonparametric approaches in the field of multivariate FFA; however, the nonparametric distribution may not always be a good-fit and capable of replacing well-implemented multivariate parametric and multivariate copula-based applications.
Comparisons of the environmental contours using C-vines with those obtained from standard multivariate copulas are also discussed.
A multivariate copula-based methodology is demonstrated that considers infiltration via the marginal distribution and solute transport via the multivariate spatial dependence structure.
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.
