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The t Copula and Related Copulas
by
Demarta, Stefano
, McNeil, Alexander J.
in
Applications
/ Clayton copula
/ Coefficients
/ Componentwise operations
/ Consistent estimators
/ Copula
/ Copula functions
/ Copulas
/ Degrees of freedom
/ Distribution functions
/ Estimation methods
/ Exact sciences and technology
/ Gumbel copula
/ Kendall's rank correlation
/ Mathematics
/ Maximum likelihood estimation
/ Multivariate analysis
/ Multivariate extreme value theory
/ Multivariate t distribution
/ Nonparametric inference
/ Probability and statistics
/ Sciences and techniques of general use
/ Statistics
/ T distribution
/ Tail dependence
2005
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The t Copula and Related Copulas
by
Demarta, Stefano
, McNeil, Alexander J.
in
Applications
/ Clayton copula
/ Coefficients
/ Componentwise operations
/ Consistent estimators
/ Copula
/ Copula functions
/ Copulas
/ Degrees of freedom
/ Distribution functions
/ Estimation methods
/ Exact sciences and technology
/ Gumbel copula
/ Kendall's rank correlation
/ Mathematics
/ Maximum likelihood estimation
/ Multivariate analysis
/ Multivariate extreme value theory
/ Multivariate t distribution
/ Nonparametric inference
/ Probability and statistics
/ Sciences and techniques of general use
/ Statistics
/ T distribution
/ Tail dependence
2005
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Do you wish to request the book?
The t Copula and Related Copulas
by
Demarta, Stefano
, McNeil, Alexander J.
in
Applications
/ Clayton copula
/ Coefficients
/ Componentwise operations
/ Consistent estimators
/ Copula
/ Copula functions
/ Copulas
/ Degrees of freedom
/ Distribution functions
/ Estimation methods
/ Exact sciences and technology
/ Gumbel copula
/ Kendall's rank correlation
/ Mathematics
/ Maximum likelihood estimation
/ Multivariate analysis
/ Multivariate extreme value theory
/ Multivariate t distribution
/ Nonparametric inference
/ Probability and statistics
/ Sciences and techniques of general use
/ Statistics
/ T distribution
/ Tail dependence
2005
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Journal Article
The t Copula and Related Copulas
2005
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Overview
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 modelling of dependent observations. Extreme value considerations are used to derive two further new copulas: the t extreme value copula is the limiting copula of componentwise maxima of t distributed random vectors; the t lower tail copula is the limiting copula of bivariate observations from a t distribution that are conditioned to lie below some joint threshold that is progressively lowered. Both these copulas may be approximated for practical purposes by simpler, better-known copulas, these being the Gumbel and Clayton copulas respectively. /// Dans cet article on décrit les propriétés de la copule t, avec particulière attention envers la dépendance des valeurs extrêmes. Exploitant la représentation de la loi multivariée t par un mélange de Gaussiennes, on construit deux nouveaux types de copule: une version biaisée (skewed t copula) et une version permettant une majeure hétérogénéité dans la modélisation des observations dépendantes (grouped t copula). Deux autres types de copule sont ensuite construits à l'aide de la théorie des valeurs extrêmes. L'une est la copule limite de la loi des maxima de chaque composante d'un vecteur aléatoire avec distribution t (t extreme value copula), l'autre est la copule limite des observations d'un vecteur bivarié obéissant à une loi t, conditionnées a être en dessous d'un certain seuil commun, qu'on baisse progressivement (t lower tail copula). En ce qui concerne les applications pratiques, ces deux dernières copules peuvent être approximées par d'autres copules plus simples et connues, comme celle de Gumbel et celle de Clayton.
Publisher
Blackwell Publishing Ltd,International Statistical Review,Blackwell,International Statistical Institute
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