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Theory of Probability and Mathematical Statistics

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Estimating multivariate extremal dependence: a new proposal


Author: M. Ferreira
Original publication: Teoriya Imovirnostei ta Matematichna Statistika, tom 93 (2015).
Journal: Theor. Probability and Math. Statist. 93 (2016), 169-175
MSC (2010): Primary 62G05; Secondary 62G32
DOI: https://doi.org/10.1090/tpms/1001
Published electronically: February 7, 2017
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Abstract: Multivariate extreme values require the use of extreme-value copulas, as they appear in the limit of componentwise maxima. These can be characterized by the so-called Pickands dependence function. A new multivariate nonparametric estimator will be presented, along with convergence properties. Based on simulations, we will analyze its performance and compare with well-known estimators from the literature.


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Additional Information

M. Ferreira
Affiliation: Center of Mathematics of University of Minho, Campus de Gualtar, Braga, Portugal
Address at time of publication: CEMAT (Center for Computational and Stochastic Mathematics) of Instituto Superior Técnico, University of Lisbon, Portugal
Email: msferreira@math.uminho.pt

DOI: https://doi.org/10.1090/tpms/1001
Keywords: Extreme value copula, multivariate Pickands dependence function, nonparametric estimation
Received by editor(s): July 31, 2015
Published electronically: February 7, 2017
Article copyright: © Copyright 2017 American Mathematical Society