An entropic view of Pickands' theorem
| dc.creator | Bercher, J. -F. | |
| dc.creator | Vignat, C. | |
| dc.date | 2008-02-21 | |
| dc.date | 2008-05-06 | |
| dc.date.accessioned | 2026-07-07T09:36:50Z | |
| dc.date.available | 2026-07-07T09:36:50Z | |
| dc.description | It is shown that distributions arising in Renyi-Tsallis maximum entropy setting are related to the Generalized Pareto Distributions (GPD) that are widely used for modeling the tails of distributions. The relevance of such modelization, as well as the ubiquity of GPD in practical situations follows from Balkema-De Haan-Pickands theorem on the distribution of excesses (over a high threshold). We provide an entropic view of this result, by showing that the distribution of a suitably normalized excess variable converges to the solution of a maximum Tsallis entropy, which is the GPD. This highlights the relevance of the so-called Tsallis distributions in many applications as well as some relevance to the use of the corresponding entropy. | |
| dc.description | 4 pages, accepted to ISIT08 | |
| dc.identifier | https://arxiv.org/abs/0802.3110 | |
| dc.identifier | http://arxiv.org/abs/0802.3110 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/160257 | |
| dc.subject | Information Theory | |
| dc.title | An entropic view of Pickands' theorem | |
| dc.type | text |