Large deviation probabilities for tail index estimators
We study the asymptotic behavior of large deviation probabilities for a general class of tail index estimators. This new class consists of the generalized version of the weighted least-squares estimators proposed by Viharos [9] and also contains the class of kernel estimators obtained by Csörgő et a...
Elmentve itt :
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| Dokumentumtípus: | Cikk |
| Megjelent: |
Bolyai Institute, University of Szeged
Szeged
2008
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| Sorozat: | Acta scientiarum mathematicarum
74 No. 1-2 |
| Kulcsszavak: | Matematika |
| Tárgyszavak: | |
| Online Access: | http://acta.bibl.u-szeged.hu/16247 |
| Tartalmi kivonat: | We study the asymptotic behavior of large deviation probabilities for a general class of tail index estimators. This new class consists of the generalized version of the weighted least-squares estimators proposed by Viharos [9] and also contains the class of kernel estimators obtained by Csörgő et al. [3]. Based on the large deviation probabilities, a comparison of the members of this class can be made. The Hill estimator turns out to have optimal rate of convergence within a subclass of estimators. |
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| Terjedelem/Fizikai jellemzők: | 413-423 |
| ISSN: | 0001-6969 |