
Stochastic Processes
About
The course gives an advanced treatment of the theory of stochastic processes based on probability theory and mathematical analysis.Hence there is a certain focus on proofs and rigour, instead of reasoning and learning by means of applications and examples. As well as being suitable for students with a more theoretical interest, the course is suitable for gaining deepened knowledge of stochastic processes for applied students with a background from one of the courses MSG800 Basic Stochastic Processes, MSG860 Basic Stochastic Processes F.
What is a stochastic process? Distribution theory. Time series with random walks. Brownian motion and diffusions. Elements of Levy processes. Gaussian processes. Stationarity and weak stationarity. Continuous time Markov chains. Elements of Queues. Self-similar processes. Elements of filtering and forecasting. Elements of simulation and numerical methods.
Prerequisites and selection
Entry requirements
An undergraduate course in mathematical statistics or a strong mathematical background.
Selection
All eligible applicants who have applied before the deadline will be granted a place.
Facilities
Mathematical 91̽»¨s is a joint department of Chalmers/University 91̽»¨. Your education takes place in the spacious and bright premises of Mathematical 91̽»¨s at the Chalmers campus Johanneberg, where there are lecture halls, computer rooms and group rooms. Here you can also find student lunch room and reading room, as well as student counsellors and student office.