Important note: The lectures will take place in SR 2.22, Mon & Tue, 8:15-9:45 am, Institute of Mathematics (building 9), Campus Golm.
The main reference is Bremaud,Markov Chains: Gibbs Fields, Monte Carlo Simulation and Queues, 2nd Edition, Springer (LINK), available as ebook via the UP library.
There is a Moodle page for the lecture (LINK) which you should enroll for (no pw needed). All further information (PDFs of the slides, zoom links, exercise sheets etc.) will be communicated via the Moodle page
See module description (LINK)
Pre-requisite to be admitted to the exam is to obtain at least 50% of the maximally achievable score of the weekly exercises. The exam will be either oral or in written (this will be decided on during the first lectures).
The course covers properties and basic types of important stochastic processes: Markov chains, martingales with discrete time, Markov processes with continuous time such as the Poisson process. A number of examples are analyzed, in particular models from physics, biology or ecology.
Students of BSc Mathematik, MSc Mathematics and other
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