Type
ArticleKAUST Department
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) DivisionStatistics Program
Date
2015-11-17Online Publication Date
2015-11-17Print Publication Date
2016-03Permanent link to this record
http://hdl.handle.net/10754/583987
Metadata
Show full item recordAbstract
The main approach to inference for multivariate extremes consists in approximating the joint upper tail of the observations by a parametric family arising in the limit for extreme events. The latter may be expressed in terms of componentwise maxima, high threshold exceedances or point processes, yielding different but related asymptotic characterizations and estimators. The present paper clarifies the connections between the main likelihood estimators, and assesses their practical performance. We investigate their ability to estimate the extremal dependence structure and to predict future extremes, using exact calculations and simulation, in the case of the logistic model.Citation
Likelihood estimators for multivariate extremes 2015 ExtremesPublisher
Springer NatureJournal
ExtremesarXiv
1411.3448Additional Links
http://link.springer.com/10.1007/s10687-015-0230-4ae974a485f413a2113503eed53cd6c53
10.1007/s10687-015-0230-4