Asymptotic behaviour of regular estimators
The P.O.T. (Peaks-Over-Threshold) approach consists of using the generalized Pareto distribution (GPD) to approximate the distribution of excesses over thresholds. We use the maximum likelihood estimators, or some other ones satisfying regularity conditions, to estimate the parameters of the approx...
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| Format: | Article |
| Language: | English |
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Instituto Nacional de Estatística | Statistics Portugal
2005-06-01
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| Series: | Revstat Statistical Journal |
| Subjects: | |
| Online Access: | https://revstat.ine.pt/index.php/REVSTAT/article/view/16 |
| _version_ | 1817997026237874176 |
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| author | Jean Diebolt Armelle Guillou |
| author_facet | Jean Diebolt Armelle Guillou |
| author_sort | Jean Diebolt |
| collection | DOAJ |
| description |
The P.O.T. (Peaks-Over-Threshold) approach consists of using the generalized Pareto distribution (GPD) to approximate the distribution of excesses over thresholds. We use the maximum likelihood estimators, or some other ones satisfying regularity conditions, to estimate the parameters of the approximating distribution. We study the asymptotic bias of these estimators and also the functional bias of the estimated GPD.
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| first_indexed | 2024-04-14T02:32:01Z |
| format | Article |
| id | doaj.art-538def404bc84ccabcc5135ab2c67b66 |
| institution | Directory Open Access Journal |
| issn | 1645-6726 2183-0371 |
| language | English |
| last_indexed | 2024-04-14T02:32:01Z |
| publishDate | 2005-06-01 |
| publisher | Instituto Nacional de Estatística | Statistics Portugal |
| record_format | Article |
| series | Revstat Statistical Journal |
| spelling | doaj.art-538def404bc84ccabcc5135ab2c67b662022-12-22T02:17:39ZengInstituto Nacional de Estatística | Statistics PortugalRevstat Statistical Journal1645-67262183-03712005-06-013110.57805/revstat.v3i1.16Asymptotic behaviour of regular estimatorsJean Diebolt 0Armelle Guillou1Université de Marne-la-ValléeUniversité Paris VI The P.O.T. (Peaks-Over-Threshold) approach consists of using the generalized Pareto distribution (GPD) to approximate the distribution of excesses over thresholds. We use the maximum likelihood estimators, or some other ones satisfying regularity conditions, to estimate the parameters of the approximating distribution. We study the asymptotic bias of these estimators and also the functional bias of the estimated GPD. https://revstat.ine.pt/index.php/REVSTAT/article/view/16extreme valuesdomain of attractionexcessesgeneralized Pareto distributionmaximum likelihood estimators |
| spellingShingle | Jean Diebolt Armelle Guillou Asymptotic behaviour of regular estimators Revstat Statistical Journal extreme values domain of attraction excesses generalized Pareto distribution maximum likelihood estimators |
| title | Asymptotic behaviour of regular estimators |
| title_full | Asymptotic behaviour of regular estimators |
| title_fullStr | Asymptotic behaviour of regular estimators |
| title_full_unstemmed | Asymptotic behaviour of regular estimators |
| title_short | Asymptotic behaviour of regular estimators |
| title_sort | asymptotic behaviour of regular estimators |
| topic | extreme values domain of attraction excesses generalized Pareto distribution maximum likelihood estimators |
| url | https://revstat.ine.pt/index.php/REVSTAT/article/view/16 |
| work_keys_str_mv | AT jeandiebolt asymptoticbehaviourofregularestimators AT armelleguillou asymptoticbehaviourofregularestimators |