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Jan Beirlant

Jan Beirlant

D-Index & Metrics

Mathematics

D-Index
43
Citations
10381
World Ranking
1669
National Ranking
21

Overview

Jan Beirlant is affiliated with KU Leuven in Belgium and has contributed extensively to the fields of mathematics, economics, econometrics, and finance. Their research primarily focuses on statistics and probability, with significant contributions to financial risk and volatility modeling, as well as statistical distribution estimation and applications.

The scientist's work is distributed among multiple subfields including statistics and probability, finance, global and planetary change, artificial intelligence, and statistical methods involving uncertainty. Key topics covered in their research include financial risk and volatility modeling, hydrology and drought analysis, advanced statistical methods and models, statistical inference, probability and risk models, and Bayesian inference methods.

The publication record features recent papers such as:

  • GENERALIZING THE LOG-MOYAL DISTRIBUTION AND REGRESSION MODELS FOR HEAVY-TAILED LOSS DATA, 2020, Astin Bulletin
  • Fitting Nonstationary Cox Processes: An Application to Fire Insurance Data, 2020, North American Actuarial Journal
  • TEMPERED PARETO-TYPE MODELLING USING WEIBULL DISTRIBUTIONS, 2021, Astin Bulletin
  • Generalized Sum Plots, 2022, Lirias (KU Leuven)
  • A new class of copula regression models for modelling multivariate heavy-tailed data, 2022, Insurance Mathematics and Economics

The frequent co-authors collaborating with Jan Beirlant include Hansjörg Albrecher, Martin Bladt, Zhengxiao Li, Andréhette Verster, and José Carlos Araujo-Acuna.

Their publications appear repeatedly in notable venues such as DOAJ (Directory of Open Access Journals), Astin Bulletin, Insurance Mathematics and Economics, Lirias (KU Leuven), and Extremes.

Best Publications

  • Statistics of Extremes: Theory and Applications

    Jan Beirlant;Yuri Goegebeur;Johan Segers;JozefL Teugels

  • Nonparametric entropy estimation. An overview

    J. Beirlant;EJ Dudewicz;László Györfi;István Dénes

  • Tail Index Estimation and an Exponential Regression Model

    Jan Beirlant;Goedele Dierckx;Yuri Goegebeur;Gunther Matthys

  • Practical analysis of extreme values

    Jan Beirlant;Jozef L. Teugels;Petra Vynckier

  • Tail Index Estimation, Pareto Quantile Plots, and Regression Diagnostics

    Jan Beirlant;Petra Vynckier;Jozef L. Teugels

  • Excess functions and estimation of the extreme-value index

    Jan Beirlant;Petra Vynckier;Josef L. Teugels

  • Actuarial statistics with generalized linear mixed models

    Katrien Antonio;Jan Beirlant

  • ESTIMATING THE EXTREME VALUE INDEX AND HIGH QUANTILES WITH EXPONENTIAL REGRESSION MODELS

    G Matthys;Jan Beirlant

  • Reinsurance: Actuarial and Statistical Aspects

    Hansjörg Albrecher;Jan Beirlant;Jozef L. Teugels

  • On exponential representations of log-spacings of extreme order statistics

    J. Beirlant;G. Dierckx;A. Guillou;C. Staăricaă

  • Estimation of the extreme-value index and generalized quantile plots

    Jan Beirlant;Goedele Dierckx;A Guillou

  • A robust estimator for the tail index of Pareto-type distributions

    B. Vandewalle;J. Beirlant;A. Christmann;M. Hubert

  • Estimation of the extreme value index and extreme quantiles under random censoring

    Jan Beirlant;Armelle Guillou;Goedele Dierckx;Amélie Fils-Villetard

  • Modeling large claims in non-life insurance

    Jan Beirlant;Jozef L. Teugels

  • HEAVY-TAILED DISTRIBUTIONS AND RATING

    J. Beirlant;G. Matthys;G. Dierckx

  • Estimating catastrophic quantile levels for heavy-tailed distributions

    Gunther Matthys;Emmanuel Delafosse;Armelle Guillou;Jan Beirlant

  • Kernel estimators for the second order parameter in extreme value statistics

    Yuri Goegebeur;Jan Beirlant;Tertius de Wet

  • Local polynomial maximum likelihood estimation for Pareto-type distributions

    Jan Beirlant;Yuri Goegebeur

  • Mean-of-order p reduced-bias extreme value index estimation under a third-order framework

    Frederico Caeiro;M. Ivette Gomes;Jan Beirlant;Jan Beirlant;Tertius de Wet

  • The mean residual life function at great age: Applications to tail estimation

    Jan Beirlant;Michel Broniatowski;Jozef L. Teugels;Petra Vynckier

  • Statistical Size Distributions in Economics and Actuarial Sciences

    Jan Beirlant

  • Universal smoothing factor selection in density estimation: theory and practice - Discussion

    Jan Beirlant

Frequent Co-Authors

Johan Segers
Johan Segers Université Catholique de Louvain
Hansjörg Albrecher
Hansjörg Albrecher University of Lausanne
László Györfi
László Györfi Budapest University of Technology and Economics
Mia Hubert
Mia Hubert KU Leuven
Jef Caers
Jef Caers Stanford University
Jan Dhaene
Jan Dhaene KU Leuven
Wim Schoutens
Wim Schoutens KU Leuven
Luc Devroye
Luc Devroye McGill University
Andrzej Kijko
Andrzej Kijko University of Pretoria

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