Lecture-day

Programme
10.00-10.15	Opening	Onno Boxma (chair of the scientific committee)
10.15-11.00	Lecture	Philippe Robert (INRIA) "Stochastic Models of communication networks: Equilibrium and Scaling Limits"
11.00-11.30	Break
11.30-12.15	Lecture	Anne Fey (Vrije Universiteit/ CWI, Amsterdam, STAR position) "Sandpile growth models, an overview"
12.15-12.45	3 Presentations	Three presentations by junior researchers within STAR: Jan-Pieter Dorsman (TU/e and CWI) Moritz Schauer (TUD and TU/e) Botond Szabó (TU/e and VU)
12.45-13.45	Lunch
13.45-14.30	Lecture	Marianne Jonker (Vrije Universiteit, Amsterdam) A frailty model for censored family survival data, applied to the age at onset of mental problems
14.30-15.00	Break
15.00-15.30	3 Presentations	Three presentations by junior researchers within STAR: Beata Roś (VU) Wioletta Ruszel (TU/e and RUN) Siamak Taati (RUG and UU)
15.30-15.45	Break
15.45-16.30	Lecture	Hans-Jörg Albrecher (Université de Lausanne) in the area of finance and statistics/stochatiscs Randomized Observation Models for the Analysis of Insurance Risk and Dividend Policies
16.30-16.35	Closing	Geurt Jongbloed, co-organizer
16.35	Reception

Participation is free of charge, however for organizational reasons, registration is obligatory.

REGISTRATION (This link will redirect you to the TU/e site, where you can register online for this lectureday)

Randomized Observation Models for the Analysis of Insurance Risk and Dividend Policies

In the framework of the classical collective model in risk theory to describe the free surplus in a portfolio of insurance contracts, the effect of random observation times at which dividends can be paid out and possible ruin can be observed is discussed. This model contains both the continuous-time and the discrete-time risk model as a limit and represents a certain type of bridge between them. This enables the explicit calculation of some quantities of interest in this context, some of them surprisingly simple. In addition, the model has some appeal on the probabilistic side as well.

A frailty model for censored family survival data, applied to the age at onset of mental problems

Family survival data are often used in genetic research to estimate genetic and environmental contributions to the age at onset of a disease or of a specific event in life. The survival data can be modeled with a correlated (gamma) frailty model. We use such a model to estimate the degree of heredity (heritability), environmental effects, and twin effects on the age at which people contact social service for the first time and to investigate whether the survival functions differ for twins and non-twins. Our data are interval censored and come from an ongoing study on health, lifestyle, and personality. Longitudinal data were collected of Dutch monozygotic and dizygotic twins and of their siblings at five time points between 1991 and 2002.