%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 }