The thesis of Robin Markwitz develops statistical frameworks for modelling interval-censored data, data where events are only partially observed within time intervals rather than as exact moments. The core model combines two stochastic processes: one describing the censoring mechanism, and another representing a point process for the event times.
Euclidean graphs
Building on concepts from stochastic processes, point process theory and measure theory, the thesis provides rigorous foundations for analyzing temporal data. Since spatial location often plays a role and may involve complex geometries, the point process is extended to Euclidean graphs, with new methods for simulation and parameter estimation.
Use in the criminology field
The developed statistical theory has significant potential to be applied in the field of criminology, as both burglaries and arson fires are often only partially observed and recorded by victims and law enforcement. Models developed in this thesis are applied to a number of simulated and real-life data sets, with the full spatio-temporal model being applied to a car arson fire data set in Enschede.
Practical
“Spatio-temporal point process models for interval-censored data”
Robin Markwitz
26 September 2025
Promotors: Prof. dr. M.N.M. van Lieshout en Prof. dr. R.J. Boucherie
