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- Publisher Website: 10.1016/j.jmva.2017.10.006
- Scopus: eid_2-s2.0-85034260290
- WOS: WOS:000418316700006
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Article: Extreme-value limit of the convolution of exponential and multivariate normal distributions: Link to the Hüsler–Reiß distribution
Title | Extreme-value limit of the convolution of exponential and multivariate normal distributions: Link to the Hüsler–Reiß distribution |
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Authors | |
Keywords | Copula Extreme-value limit Parametric bootstrap Parsimonious dependence |
Issue Date | 2018 |
Publisher | Elsevier. The Journal's web site is located at http://www.elsevier.com/locate/jmva |
Citation | Journal of Multivariate Analysis, 2018, v. 163, p. 80-95 How to Cite? |
Abstract | The multivariate Hüsler–Reiß copula is obtained as a direct extreme-value limit from the convolution of a multivariate normal random vector and an exponential random variable multiplied by a vector of constants. It is shown how the set of Hüsler–Reiß parameters can be mapped to the parameters of this convolution model. Assuming there are no singular components in the Hüsler–Reiß copula, the convolution model leads to exact and approximate simulation methods. An application of simulation is to check if the Hüsler–Reiß copula with different parsimonious dependence structures provides adequate fit to some data consisting of multivariate extremes. |
Persistent Identifier | http://hdl.handle.net/10722/259498 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Krupskii, P | - |
dc.contributor.author | Joe, H | - |
dc.contributor.author | Lee, D | - |
dc.contributor.author | Genton, MG | - |
dc.date.accessioned | 2018-09-03T04:08:47Z | - |
dc.date.available | 2018-09-03T04:08:47Z | - |
dc.date.issued | 2018 | - |
dc.identifier.citation | Journal of Multivariate Analysis, 2018, v. 163, p. 80-95 | - |
dc.identifier.uri | http://hdl.handle.net/10722/259498 | - |
dc.description.abstract | The multivariate Hüsler–Reiß copula is obtained as a direct extreme-value limit from the convolution of a multivariate normal random vector and an exponential random variable multiplied by a vector of constants. It is shown how the set of Hüsler–Reiß parameters can be mapped to the parameters of this convolution model. Assuming there are no singular components in the Hüsler–Reiß copula, the convolution model leads to exact and approximate simulation methods. An application of simulation is to check if the Hüsler–Reiß copula with different parsimonious dependence structures provides adequate fit to some data consisting of multivariate extremes. | - |
dc.language | eng | - |
dc.publisher | Elsevier. The Journal's web site is located at http://www.elsevier.com/locate/jmva | - |
dc.relation.ispartof | Journal of Multivariate Analysis | - |
dc.subject | Copula | - |
dc.subject | Extreme-value limit | - |
dc.subject | Parametric bootstrap | - |
dc.subject | Parsimonious dependence | - |
dc.title | Extreme-value limit of the convolution of exponential and multivariate normal distributions: Link to the Hüsler–Reiß distribution | - |
dc.type | Article | - |
dc.identifier.email | Lee, D: leedav@hku.hk | - |
dc.identifier.authority | Lee, D=rp02276 | - |
dc.identifier.doi | 10.1016/j.jmva.2017.10.006 | - |
dc.identifier.scopus | eid_2-s2.0-85034260290 | - |
dc.identifier.hkuros | 288841 | - |
dc.identifier.volume | 163 | - |
dc.identifier.spage | 80 | - |
dc.identifier.epage | 95 | - |
dc.identifier.isi | WOS:000418316700006 | - |