A high quantile estimator based on the log-generalized Weibull tail limit
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DOI: 10.1016/j.ecosta.2017.03.001
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- de Valk, Cees Fouad & Cai, Juan-Juan, 2018. "A high quantile estimator based on the log-generalized Weibull tail limit," LIDAM Reprints ISBA 2018030, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
References listed on IDEAS
- Einmahl, J. H.J. & Dekkers, A. L.M. & de Haan, L., 1989. "A moment estimator for the index of an extreme-value distribution," Other publications TiSEM 81970cb3-5b7a-4cad-9bf6-2, Tilburg University, School of Economics and Management.
- Drees, Holger & Kaufmann, Edgar, 1998. "Selecting the optimal sample fraction in univariate extreme value estimation," Stochastic Processes and their Applications, Elsevier, vol. 75(2), pages 149-172, July.
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Cited by:
- Albert, Clément & Dutfoy, Anne & Gardes, Laurent & Girard, Stéphane, 2020. "An extreme quantile estimator for the log-generalized Weibull-tail model," Econometrics and Statistics, Elsevier, vol. 13(C), pages 137-174.
- Matheus Henrique Junqueira Saldanha & Adriano Kamimura Suzuki, 2023. "On dealing with the unknown population minimum in parametric inference," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(3), pages 509-535, September.
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Keywords
High quantile; Hill estimator; Log-generalized Weibull tail limit; Log-GW tail index;All these keywords.
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