66 citations · 121 across the 5 of their papers we have counts for
5 papers
Modeling the occurrence of events subject to a reporting delay via an EM algorithm
Roel Verbelen, Katrien Antonio, Gerda Claeskens +1
A delay between the occurrence and the reporting of events often has practical implications such as for the amount of capital to hold for insurance companies, or for taking prevent…
Boosting insights in insurance tariff plans with tree-based machine learning methods
Roel Henckaerts, Marie-Pier Côté, Katrien Antonio +1
Pricing actuaries typically operate within the framework of generalized linear models (GLMs). With the upswing of data analytics, our study puts focus on machine learning methods t…
Sparse Regression with Multi-type Regularized Feature Modeling
Sander Devriendt, Katrien Antonio, Tom Reynkens +1
Within the statistical and machine learning literature, regularization techniques are often used to construct sparse (predictive) models. Most regularization strategies only work f…
Modeling the number of hidden events subject to observation delay
Jonas Crevecoeur, Katrien Antonio, Roel Verbelen
This paper considers the problem of predicting the number of events that have occurred in the past, but which are not yet observed due to a delay. Such delayed events are relevant…
Modelling Censored Losses Using Splicing: a Global Fit Strategy With Mixed Erlang and Extreme Value Distributions
Tom Reynkens, Roel Verbelen, Jan Beirlant +1
In risk analysis, a global fit that appropriately captures the body and the tail of the distribution of losses is essential. Modelling the whole range of the losses using a standar…