Modeling the occurrence of events subject to a reporting delay via an EM algorithm

We present a flexible regression framework to jointly estimate the occurrence and reporting of events from data at daily level.

Modeling the number of hidden events subject to observation delay

We propose a new method to model the number of events that occurred in the past, but which are not yet registered due to an observation delay. Our approach provides an elegant and flexible framework for modeling the observation delay subject to calendar day covariates by introducing the concept of observation exposure.

Data analytics for insurance loss modelling, telematics pricing and claims reserving.

PhD Thesis