Displaying similar documents to “On approximation of copulas.”

Markov operators and n-copulas

P. Mikusiński, M. D. Taylor (2009)

Annales Polonici Mathematici

Similarity:

We extend the definition of Markov operator in the sense of J. R. Brown and of earlier work of the authors to a setting appropriate to the study of n-copulas. Basic properties of this extension are studied.

Multivariate Markov Families of Copulas

Ludger Overbeck, Wolfgang M. Schmidt (2015)

Dependence Modeling

Similarity:

For the Markov property of a multivariate process, a necessary and suficient condition on the multidimensional copula of the finite-dimensional distributions is given. This establishes that the Markov property is solely a property of the copula, i.e., of the dependence structure. This extends results by Darsow et al. [11] from dimension one to the multivariate case. In addition to the one-dimensional case also the spatial copula between the different dimensions has to be taken into account....

On dependence structure of copula-based Markov chains

Martial Longla (2014)

ESAIM: Probability and Statistics

Similarity:

We consider dependence coefficients for stationary Markov chains. We emphasize on some equivalencies for reversible Markov chains. We improve some known results and provide a necessary condition for Markov chains based on Archimedean copulas to be exponential -mixing. We analyse the example of the Mardia and Frechet copula families using small sets.

Invariant copulas

Erich Peter Klement, Radko Mesiar, Endre Pap (2002)

Kybernetika

Similarity:

Constructing copulas by means of pairs of order statistics

Ali Dolati, Manuel Úbeda-Flores (2009)

Kybernetika

Similarity:

In this paper, we introduce two transformations on a given copula to construct new and recover already-existent families. The method is based on the choice of pairs of order statistics of the marginal distributions. Properties of such transformations and their effects on the dependence and symmetry structure of a copula are studied.

Shuffles of Min.

Piotr Mikusinski, Howard Sherwood, Michael D. Taylor (1992)

Stochastica

Similarity:

Copulas are functions which join the margins to produce a joint distribution function. A special class of copulas called shuffles of Min is shown to be dense in the collection of all copulas. Each shuffle of Min is interpreted probabilistically. Using the above-mentioned results, it is proved that the joint distribution of any two continuously distributed random variables X and Y can be approximated uniformly, arbitrarily closely by the joint distribution of another pair X* and Y* each...

Norms for copulas.

Darsow, William F., Olsen, Elwood T. (1995)

International Journal of Mathematics and Mathematical Sciences

Similarity: