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, ...

As global financial markets become increasingly interconnected, accurately modelling correlations between assets is essential. Traditional models often assume static correlations, which fail to ...

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 ...

This course provides doctoral students the foundations of applied probability and stochastic modeling. The first part of the course covers basic concepts in probability, such as the Borel Cantelli ...

Systematic study of Markov chains and some of the simpler Markov processes including renewal theory, limit theorems for Markov chains, branching processes, queuing theory, birth and death processes, ...

The Annals of Probability, Vol. 1, No. 4 (Aug., 1973), pp. 674-689 (16 pages) This paper shows that the epsilon entropy in the sup norm of a wide variety of processes with continuous paths on the unit ...

This is a preview. Log in through your library . Abstract In this paper we use point processes to model a simple stochastic epidemic with relapse, using the information given by the times in which a ...