Stochastic processes provide a rigorous framework for modelling systems that evolve over time under uncertainty, while extremal theory offers the tools for understanding the behaviour of rare, ...

Editor's note: As the following article is a chapter (Chapter 8) from David Koenig's book, Practical Control Engineering: Guide for Engineers, Managers, and Practitioners (MATLAB Examples) (McGraw ...

Simulation research derives new methods for the design, analysis, and optimization of simulation experiments. Research on stochastic models develops and analyzes models of systems with random behavior ...

The study of gradient flows and large deviations in stochastic processes forms a vital link between microscopic randomness and macroscopic determinism. By characterising how systems evolve in response ...

The paper investigates stochastic processes directed by a randomized time process. A new family of directing processes called Hougaard processes is introduced. Monotonicity properties preserved under ...

Graduate standing, or permission of instructor. Statistics, and real analysis at the undergraduate engineering or mathematics level; graduate level probability and stochastic processes (IEMS 460-1); ...

A cylindrical Lévy process does not enjoy a cylindrical version of the semimartingale decomposition which results in the need to develop a completely novel approach to stochastic integration. In this ...

This course is compulsory on the BSc in Actuarial Science. This course is available on the BSc in Data Science, BSc in Financial Mathematics and Statistics, BSc in Mathematics with Data Science, BSc ...