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Communications in Statistics - Theory and Methods Volume 39, 2010 - Issue 7
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Original Articles

Peaks-Over-Threshold Modeling Under Random Censoring

Jan Beirlant Department of Mathematics and Leuven Statistics Center, University of Leuven, France
,
Armelle Guillou Institute de Recherche Mathématique Avancée, Université de Strasbourg et CNRS, Strasbourg, FranceCorrespondence[email protected]
&
Gwladys Toulemonde I3M, Université de Montpellier 2, Montpellier, France
Pages 1158-1179 | Received 17 Jun 2008, Accepted 27 Feb 2009, Published online: 22 Mar 2010

Citations (17)

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Read on this site (3)

Julien Worms & Rym Worms. (2021) Estimation of extremes for heavy-tailed and light-tailed distributions in the presence of random censoring. Statistics 55:5, pages 979-1017.
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Ion Grama & Kévin Jaunâtre. (2019) Estimation of extreme survival probabilities with cox model. Statistics 53:4, pages 807-838.
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Jan Beirlant, Ségolen Geffray & Armelle Guillou. (2011) Estimation of the Bias of the Maximum Likelihood Estimators in an Extreme Value Context. Communications in Statistics - Theory and Methods 40:22, pages 3959-3971.
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Articles from other publishers (14)

Mikael Escobar-Bach & Ingrid Van Keilegom. (2023) Nonparametric estimation of conditional cure models for heavy-tailed distributions and under insufficient follow-up. Computational Statistics & Data Analysis 183, pages 107728.
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Mickaël De Backer, Catherine Legrand, Julien Péron, Alexandre Lambert & Marc Buyse. (2022) On the use of extreme value tail modeling for generalized pairwise comparisons with censored outcomes. Pharmaceutical Statistics 22:2, pages 284-299.
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Martin Bladt, Hansjörg Albrecher & Jan Beirlant. (2021) Trimmed extreme value estimators for censored heavy-tailed data. Electronic Journal of Statistics 15:1.
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Julien Worms & Rym Worms. (2019) Estimation of extremes for Weibull-tail distributions in the presence of random censoring. Extremes 22:4, pages 667-704.
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Gilles Stupfler. (2019) On a relationship between randomly and non-randomly thresholded empirical average excesses for heavy tails. Extremes 22:4, pages 749-769.
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Gilles Stupfler. (2018) On the study of extremes with dependent random right-censoring. Extremes 22:1, pages 97-129.
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Jitao Yao, Hui Gu & Liuzhuo Chen. (2018) Probability Analysis of Crane Load and Load Combination Actions. Mathematical Problems in Engineering 2018, pages 1-13.
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Abdelkader Ameraoui, Kamal Boukhetala & Jean-François Dupuy. (2016) Bayesian estimation of the tail index of a heavy tailed distribution under random censoring. Computational Statistics & Data Analysis 104, pages 148-168.
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Gilles Stupfler. (2016) Estimating the conditional extreme-value index under random right-censoring. Journal of Multivariate Analysis 144, pages 1-24.
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Pathé Ndao, Aliou Diop & Jean-François Dupuy. (2016) Nonparametric estimation of the conditional extreme-value index with random covariates and censoring. Journal of Statistical Planning and Inference 168, pages 20-37.
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M. Ivette Gomes & Armelle Guillou. (2014) Extreme Value Theory and Statistics of Univariate Extremes: A Review. International Statistical Review 83:2, pages 263-292.
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Laurent Gardes & Gilles Stupfler. (2014) Estimating extreme quantiles under random truncation. TEST 24:2, pages 207-227.
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Pathé Ndao, Aliou Diop & Jean-François Dupuy. (2014) Nonparametric estimation of the conditional tail index and extreme quantiles under random censoring. Computational Statistics & Data Analysis 79, pages 63-79.
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Julien Worms & Rym Worms. (2014) New estimators of the extreme value index under random right censoring, for heavy-tailed distributions. Extremes 17:2, pages 337-358.
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