Results 11 to 20 of about 24,138 (305)

Is a Normal Copula the Right Copula? [PDF]

open access: yesJournal of Business & Economic Statistics, 2018
We derive computationally simple and intuitive expressions for score tests of Gaussian copulas against Generalized Hyperbolic alternatives, including symmetric and asymmetric Student t, and many other examples. We decompose our tests into third and fourth moment components, and obtain one-sided Likelihood Ratio analogues, whose standard asymptotic ...
Amengual, Dante, Sentana, Enrique
openaire   +2 more sources

Sibuya copulas [PDF]

open access: yesJournal of Multivariate Analysis, 2013
23 pages, 3 ...
Marius Hofert, Frédéric Vrins
openaire   +2 more sources

Multivariate copulas, quasi-copulas and lattices [PDF]

open access: yesStatistics & Probability Letters, 2011
We investigate some properties of the partially ordered sets of multivariate copulas and quasi-copulas. Whereas the set of bivariate quasi-copulas is a complete lattice, which is order-isomorphic to the Dedekind-MacNeille completion of the set of bivariate copulas, we show that this is not the case in higher dimensions.
Fernández-Sánchez, Juan   +2 more
openaire   +3 more sources

Trivariate copula to design coastal structures [PDF]

open access: yesNatural Hazards and Earth System Sciences, 2021
Some coastal structures must be redesigned in the future due to rising sea levels caused by climate change. The design of structures subjected to the actions of waves requires an accurate estimate of the long return period of such parameters as wave ...
O. Orcel, P. Sergent, F. Ropert
doaj   +1 more source

Bayesian Nonparametric Inference for a Multivariate Copula Function [PDF]

open access: yes, 2014
The paper presents a general Bayesian nonparametric approach for estimating a high dimensional copula. We first introduce the skew-normal copula, which we then extend to an infinite mixture model.
Wu, Juan, Wang, Xue, Walker, Stephen G.
core   +1 more source

The t Copula and Related Copulas

open access: yesInternational Statistical Review, 2007
Summary: The \(t\) copula and its properties are described with a focus on issues related to the dependence of extreme values. The Gaussian mixture representation of a multivariate \(t\) distribution is used as a starting point to construct two new copulas, the skewed \(t\) copula and the grouped \(t\) copula, which allow more heterogeneity in the ...
Demarta, Stefano, Mcneil, Alexander J.
openaire   +3 more sources

Quasi-Copulas, Copulas and Fuzzy Implicators

open access: yesInternational Journal of Computational Intelligence Systems, 2020
In this paper, we study relations between fuzzy implicators and some kinds of fuzzy conjunctors, in particular, quasi-copulas and copulas. We show that there is a one-to-one correspondence between the classes of all quasi-copulas and 1-Lipschitz fuzzy implicators.
Radko Mesiar, Anna Kolesárová
openaire   +2 more sources

Pair-copula constructions of multiple dependence [PDF]

open access: yes, 2006
Building on the work of Bedford, Cooke and Joe, we show how multivariate data, which exhibit complex patterns of dependence in the tails, can be modelled using a cascade of pair-copulae, acting on two variables at a time.
Aas, Kjersti   +3 more
core   +1 more source

A Functional for Copulas and Quasi-Copulas [PDF]

open access: yesISRN Probability and Statistics, 2012
We recall and study some properties of a known functional operating on the set of n-copulas and determine conditions under such functional is well defined on the set of n-quasi-copulas. As a consequence, new families of copulas and quasi-copulas are defined, illustrating our results with several examples.
openaire   +2 more sources

The Structure of the Class of Maximum Tsallis–Havrda–Chavát Entropy Copulas

open access: yesEntropy, 2016
A maximum entropy copula is the copula associated with the joint distribution, with prescribed marginal distributions on [ 0 , 1 ] , which maximizes the Tsallis–Havrda–Chavát entropy with q = 2 .
Jesús E. García   +2 more
doaj   +1 more source

Home - About - Disclaimer - Privacy