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%0 Journal Article
%1 frigessi2002dynamic
%A Frigessi, Arnoldo
%A Haug, Ola
%A Rue, Håvard
%D 2002
%I Kluwer Academic Publishers
%J Extremes
%K extremes mixture threshold
%N 3
%P 219-235
%R 10.1023/A:1024072610684
%T A Dynamic Mixture Model for Unsupervised Tail Estimation without Threshold Selection
%U http://dx.doi.org/10.1023/A%3A1024072610684
%V 5
%X Exceedances over high thresholds are often modeled by fitting a generalized Pareto distribution (GPD) on R
@article{frigessi2002dynamic,
abstract = {Exceedances over high thresholds are often modeled by fitting a generalized Pareto distribution (GPD) on R},
added-at = {2013-03-05T21:08:07.000+0100},
author = {Frigessi, Arnoldo and Haug, Ola and Rue, Håvard},
biburl = {https://www.bibsonomy.org/bibtex/282fd559877daaa695d826ccf45b7a1d1/marsianus},
description = {A Dynamic Mixture Model for Unsupervised Tail Estimation without Threshold Selection - Springer},
doi = {10.1023/A:1024072610684},
interhash = {83934424a456e45bd977607fb1865f0c},
intrahash = {82fd559877daaa695d826ccf45b7a1d1},
issn = {1386-1999},
journal = {Extremes},
keywords = {extremes mixture threshold},
language = {English},
number = 3,
pages = {219-235},
publisher = {Kluwer Academic Publishers},
timestamp = {2013-03-05T21:08:07.000+0100},
title = {A Dynamic Mixture Model for Unsupervised Tail Estimation without Threshold Selection},
url = {http://dx.doi.org/10.1023/A%3A1024072610684},
volume = 5,
year = 2002
}