Universität Wien

250068 VO Stochastic processes (2021W)

5.00 ECTS (3.00 SWS), SPL 25 - Mathematik
MIXED

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Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

Language: English

Examination dates

Lecturers

Classes (iCal) - next class is marked with N

  • Friday 01.10. 12:30 - 13:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 07.10. 09:45 - 11:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 08.10. 12:30 - 13:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 14.10. 09:45 - 11:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 15.10. 12:30 - 13:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 21.10. 09:45 - 11:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 22.10. 12:30 - 13:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 28.10. 09:45 - 11:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 29.10. 12:30 - 13:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 04.11. 09:45 - 11:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 05.11. 12:30 - 13:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 11.11. 09:45 - 11:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 12.11. 12:30 - 13:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 18.11. 09:45 - 11:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 19.11. 12:30 - 13:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 25.11. 09:45 - 11:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 26.11. 12:30 - 13:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 02.12. 09:45 - 11:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 03.12. 12:30 - 13:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 09.12. 09:45 - 11:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 10.12. 12:30 - 13:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 16.12. 09:45 - 11:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 17.12. 12:30 - 13:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 07.01. 12:30 - 13:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 13.01. 09:45 - 11:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 14.01. 12:30 - 13:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 20.01. 09:45 - 11:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 21.01. 12:30 - 13:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 28.01. 12:30 - 13:15 Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock

Information

Aims, contents and method of the course

Stochastic processes describe the evolution of systems subject to randomness.
The simplest example of such systems are Markov chains, in which only information about the present state is retained for the future evolution.
Although these are simple to describe and arise in a large number of applications, there is a surprisingly rich theory describing the behaviour of such systems in the large time limit.

After discussing Markov chains in discrete time and discrete space, we will move on to the notion of martingale. This
fundamental concept plays the same role for stochastic processes that "constants of motion'' play in physics.

Assessment and permitted materials

Written exam

Minimum requirements and assessment criteria

50% at written exam required for pass grade.

Examination topics

Markov chains: recurrence, transience, invariant measure, convergence to equilibrium.
Martinagles: stopping times, optional stopping, convergence theorem.

Reading list

James Norris: Markov chains. Cambridge University Press.

Association in the course directory

MBIP; MSTP

Last modified: Fr 25.11.2022 09:08