Course content

Markov processes with discrete/continuous time-parameter and discrete/continuous state space, including branching processes, Poisson processes, birth and death processes, and Brownian motion. Queueing processes. Procedures for simulation of stochastic processes.

Learning outcome

The objective of the course is to give the students basic knowledge in stochastic processes with reference in time, in particular different types of Markov processes. Through the exercises the students become capable of applying this in calculations.

Learning methods and activities

Lectures and a project/term paper. Portfolio assessment is the basis for the grade awarded in the course. This portfolio comprises a written final examination 80% and the semester assignment 20%. The results for the constituent parts are to be given in %-points, while the grade for the whole portfolio (course grade) is given by the letter grading system. Retake of examination may be given as an oral examination. The lectures will be given in English if they are attended by students
from the Master's Programme in Mathematics for International Students.

Compulsory assignments

• Exercise

Recommended previous knowledge

The course is based on TMA4240/TMA4245 Statistics or equivalent.

Course materials

S. M. Ross: Introduction to probability models, Academic Press.

Credit reductions