On Exponential Representations of Log-Spacings of Extreme Order Statistics

By Jan Beirlant, Goedele Dierckx, Armelle Guillou, C. Staăricaă. 2002

116 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/c65af4168ceecba2786645e22ab5722354fe3637

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Citations in the corpus

Quasi-Conjugate Bayes Estimates for GPD Parameters and Application to Heavy Tails Modelling (2005, methodology): “Since Gamcon II densities have gamma-like tails (see the comments after (5) in Subsection 2.”
A robust prediction error criterion for pareto modelling of upper tails (2005, methodology): “Results based on 100 replications were reported by Beirlant et al. (2002) for Methods 2-5 and a sample size of n = 500.”
A moving window approach for nonparametric estimation of the conditional tail index (2008, background): “Similar results can be found in [14] for rescaled log-spacings of Weibull-type random variables, and in [3] in the case of Pareto-type random variables without covariate.”
Estimation of the extreme-value index and generalized quantile plots (2005, methodology): “We follow the same procedure as in Beirlant et al. (2002).”
Bias-reduced estimators of the Weibull tail-coefficient (2008, unknown): “This exponential regression model is similar to the ones proposed by Beirlant et al. (1999, 2002) and Feuerverger and Hall (1999) e The full model (5) allows us to generate bias-corrected estimates b θ n for θ through maximum likelihood estimation of θ , b (log n / k n ) and ρ for each 1 ≤ k n ≤ n…”
Extreme Value Analysis: an Introduction (2013, methodology): “…plot is estimated by (see Beirlant et al. (2004a) Section 5.2) and another Zipf estimate based on unconstrained least square regression (see Beirlant et al. (2002, 2004a), Section 5.2) One of the main interests of this last estimator is its smoothness as a function of k , which in some…”
Conditional extremes from heavy-tailed distributions: an application to the estimation of extreme rainfall return levels (2010, background): “In order to be self-contained, we quote a lemma proved in (Beirlant et al. 2002).”
Threshold Selection in Extreme Value Analysis (2016, methodology): “pirical mean-excess and sum-plots Zipf, Hill, empirical mean-excess and sum plots can be found in Beirlant, Goegebeur, Segers and Teugels ([5]), among others.”