Project level: PhD

Spatial processes are mathematical models for spatial data; that is, spatially arranged measurements and patterns. Spatial processes come in many different forms and shapes, ranging from point processes to Markov random fields. The availability of fast computers and advances in Monte Carlo simulation methods have greatly enhanced the understanding of spatial processes. However, the analysis of spatial processes under extreme conditions is still not well understood. The purpose of this project is to develop new theory and applications for the efficient simulation of spatial processes conditioned on rare events.

Project members

Professor Dirk Kroese

School of Mathematics and Physics