# Stochastic Modelling

Stochastic modelling is the science of the mathematical representation of processes and systems evolving randomly, the study of their probabilistic structure and the statistical analysis of unknown features in the models. It is a broad and interdisciplinary tool combining mathematics, computer intensive methods, statistical inference and applied probability. Applications are available in many research areas, such as biology, ecology, medicine, finance, telecommunication, climate science, neurophysiology, detector physics, chemical kinetics and others.

The Centre for Mathematical Sciences at Lund University is involved with an extensive range of applications and theoretical research in stochastic modelling, including:

Spatio-temporal stochastic modelling with applications in extreme value analysis, fatigue and risk analysis, and analysis of environment, climate and oceanographic data.

Statistical inference for complex systems using computer intensive Monte Carlo methods, such as sequential Monte Carlo, Markov chains Monte Carlo and likelihood-free methods for Bayesian inference.

Statistical inference for stochastic differential equation models and Lévy processes with applications in biology. See also the Financial mathematics group.

Please visit the staff's pages in the column to the right for more information.