On the maximum likelihood estimator for the generalized extreme-value distribution
| dc.contributor.author | Bücher, Axel | |
| dc.contributor.author | Segers, Johan | |
| dc.date.accessioned | 2016-01-26T11:34:23Z | |
| dc.date.available | 2016-01-26T11:34:23Z | |
| dc.date.issued | 2016 | |
| dc.description.abstract | The vanilla method in univariate extreme-value theory consists of fitting the three-parameter Generalized Extreme-Value (GEV) distribution to a sample of block maxima. Despite claims to the contrary, the asymptotic normality of the maximum likelihood estimator has never been established. In this paper, a formal proof is given using a general result on the maximum likelihood estimator for parametric families that are differentiable in quadratic mean but whose support depends on the parameter. An interesting side result concerns the (lack of) differentiability in quadratic mean of the GEV family. | en |
| dc.identifier.uri | http://hdl.handle.net/2003/34470 | |
| dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-16526 | |
| dc.language.iso | en | de |
| dc.relation.ispartofseries | Discussion Paper / SFB 823;3/2016 | en |
| dc.subject | differentiability in quadratic mean | en |
| dc.subject | support | en |
| dc.subject | Lipschitz condition | en |
| dc.subject | generalized extreme-value distribution | en |
| dc.subject | Fisher information | en |
| dc.subject | empirical process | en |
| dc.subject | maximum likelihood | en |
| dc.subject | M-estimator | en |
| dc.subject.ddc | 310 | |
| dc.subject.ddc | 330 | |
| dc.subject.ddc | 620 | |
| dc.title | On the maximum likelihood estimator for the generalized extreme-value distribution | en |
| dc.type | Text | de |
| dc.type.publicationtype | workingPaper | de |
| dcterms.accessRights | open access |