34 citations · 37 across the 4 of their papers we have counts for
5 papers
Estimating the maximum possible earthquake magnitude using extreme value methodology: the Groningen case
Jan Beirlant, Andrzej Kijko, Tom Reynkens +1
The area-characteristic, maximum possible earthquake magnitude is required by the earthquake engineering community, disaster management agencies and the insurance industry. T…
Penalized bias reduction in extreme value estimation for censored Pareto-type data, and long-tailed insurance applications
Jan Beirlant, Gaonyalelwe Maribe, Andrehette Verster
The subject of tail estimation for randomly censored data from a heavy tailed distribution receives growing attention, motivated by applications for instance in actuarial statistic…
Reducing MSE in estimation of heavy tails: a Bayesian approach
Gaonyalelwe Maribe, Andréhette Verster, Jan Beirlant
Bias reduction in tail estimation has received considerable interest in extreme value analysis. Estimation methods that minimize the bias while keeping the mean squared error (MSE)…
Tail fitting for truncated and non-truncated Pareto-type distributions
Jan Beirlant, Isabel Fraga Alves, Ivette Gomes
Recently some papers, such as Aban, Meerschaert and Panorska (2006), Nuyts (2010) and Clark (2013), have drawn attention to possible truncation in Pareto tail modelling. Sometimes…
Second-order refined peaks-over-threshold modelling for heavy-tailed distributions
Jan Beirlant, Elisabeth Joossens, Johan Segers
Modelling excesses over a high threshold using the Pareto or generalized Pareto distribution (PD/GPD) is the most popular approach in extreme value statistics. This method typicall…