Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Statistics of Extremes
2004756 citationsJan Beirlant, Yuri Goegebeur et al.profile →
This map shows the geographic impact of Jan Beirlant's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jan Beirlant with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jan Beirlant more than expected).
This network shows the impact of papers produced by Jan Beirlant. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jan Beirlant. The network helps show where Jan Beirlant may publish in the future.
Co-authorship network of co-authors of Jan Beirlant
This figure shows the co-authorship network connecting the top 25 collaborators of Jan Beirlant.
A scholar is included among the top collaborators of Jan Beirlant based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Jan Beirlant. Jan Beirlant is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Goegebeur, Yuri, Jan Beirlant, & Tertius de Wet. (2008). LINKING PARETO-TAIL KERNEL GOODNESS-OF-FIT STATISTICS WITH TAIL INDEX AT OPTIMAL THRESHOLD AND SECOND ORDER ESTIMATION. Digital Access to Libraries. 6(1). 51–69.33 indexed citations
8.
Beirlant, Jan, et al.. (2008). Predicting high quantiles through the Dirichlet process on extreme modelling. 42(2). 101–124.
9.
Antonio, Katrien & Jan Beirlant. (2005). Applications of Generalized Linear Mixed Models in Actuarial Statistics.2 indexed citations
Antonio, Katrien, et al.. (2005). A general bootstrap approach to deal with zero and negative values in stochastic claims reserving. Insurance Mathematics and Economics. 37(2). 383–383.1 indexed citations
13.
Beirlant, Jan & Yuri Goegebeur. (2004). Discussion of the paper 'A conditional approach for multivariate extreme values' by Heffernan, J.E. & J.A. Tawn. Journal of the Royal Statistical Society Series B (Statistical Methodology). 66(539).2 indexed citations
14.
Matthys, Gunther & Jan Beirlant. (2003). ESTIMATING THE EXTREME VALUE INDEX AND HIGH QUANTILES WITH EXPONENTIAL REGRESSION MODELS. Statistica Sinica. 13(3). 853–880.52 indexed citations
15.
Beirlant, Jan, et al.. (2002). Modelling excesses over high thresholds by perturbed generalized Pareto distributions. Data Archiving and Networked Services (DANS). 2002030(2). 167–70.1 indexed citations
16.
Beirlant, Jan, Jozef L. Teugels, & Petra Vynckier. (1996). Practical analysis of extreme values.165 indexed citations
Beirlant, Jan & Lajos Horváth. (1984). Approximations of m-overlapping spacings processes. Scandinavian Journal of Statistics. 11(4). 225–245.3 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.