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    Likelihood estimators for multivariate extremes

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    MultivariateExtremes2.pdf
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    Description:
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    Type
    Article
    Authors
    Huser, Raphaël cc
    Davison, Anthony C.
    Genton, Marc G. cc
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Statistics Program
    Date
    2015-11-17
    Online Publication Date
    2015-11-17
    Print Publication Date
    2016-03
    Permanent link to this record
    http://hdl.handle.net/10754/583987
    
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    Abstract
    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 Extremes
    Publisher
    Springer Nature
    Journal
    Extremes
    DOI
    10.1007/s10687-015-0230-4
    arXiv
    1411.3448
    Additional Links
    http://link.springer.com/10.1007/s10687-015-0230-4
    ae974a485f413a2113503eed53cd6c53
    10.1007/s10687-015-0230-4
    Scopus Count
    Collections
    Articles; Statistics Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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