dc.contributor.author |
Bahraoui, Zuhair |
dc.contributor.author |
Bolancé, Catalina |
dc.contributor.author |
Pérez-Marín, Ana M.. |
dc.date |
2014 |
dc.identifier |
https://ddd.uab.cat/record/118912 |
dc.identifier |
urn:oai:ddd.uab.cat:118912 |
dc.identifier |
urn:articleid:20138830v38n1p89 |
dc.identifier |
urn:oai:raco.cat:article/277220 |
dc.format |
application/pdf |
dc.language |
eng |
dc.publisher |
|
dc.relation |
SORT : statistics and operations research transactions ; Vol. 38, Núm. 1 (January-June 2014), p. 89-102 |
dc.rights |
open access |
dc.rights |
Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades. |
dc.rights |
https://creativecommons.org/licenses/by-nc-nd/3.0/ |
dc.subject |
Extreme value copula |
dc.subject |
Extreme value distributions |
dc.subject |
Quantile |
dc.title |
Testing extreme value copulas to estimate the quantile |
dc.type |
Article |
dc.description.abstract |
We generalize the test proposed by Kojadinovic, Segers and Yan which is used for testing whether the data belongs to the family of extreme value copulas. We prove that the generalized test can be applied whatever the alternative hypothesis. We also study the effect of using different extreme value copulas in the context of risk estimation. To measure the risk we use a quantile. Our results have been motivated by a bivariate sample of losses from a real database of auto insurance claims. |