Multivariate Archimax copulas
DOI10.1016/j.jmva.2013.12.013zbMath1349.62173OpenAlexW2059296920MaRDI QIDQ2438634
Arthur Charpentier, Anne-Laure Fougères, Christian Genest, Johanna G. Nešlehová
Publication date: 6 March 2014
Published in: Journal of Multivariate Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jmva.2013.12.013
domain of attractionArchimedean copulastable tail dependence functionmultivariate extreme-value distributionWilliamson \(d\)-transform
Characterization and structure theory for multivariate probability distributions; copulas (62H05) Extreme value theory; extremal stochastic processes (60G70) Statistics of extreme values; tail inference (62G32) Characteristic functions; other transforms (60E10)
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- Dense classes of multivariate extreme value distributions
- Homogeneous distributions -- and a spectral representation of classical mean values and stable tail dependence functions
- Efficiently sampling nested Archimedean copulas
- An introduction to copulas.
- Multivariate Archimedean copulas, \(d\)-monotone functions and \(\ell _{1}\)-norm symmetric distributions
- A characterization of Gumbel's family of extreme value distributions
- Orthant tail dependence of multivariate extreme value distributions
- From Archimedean to Liouville copulas
- On Pickands coordinates in arbitrary dimensions
- Simulating multivariate extreme value distributions of logistic type
- Multivariate distributions from mixtures of max-infinitely divisible distributions
- Default models based on scale mixtures of Marshall-Olkin copulas: properties and applications
- Bivariate distributions with given extreme value attractor
- \(d\)-dimensional dependence functions and Archimax copulas
- Max-stable models for multivariate extremes
- Extremal behavior of Archimedean copulas
- Families of Multivariate Distributions
- Statistics of Extremes
- Simulation of multivariate extreme values
- A characterization of absolutely monotonic (Δ) functions
- A TRACTABLE MULTIVARIATE DEFAULT MODEL BASED ON A STOCHASTIC TIME-CHANGE