Monte Carlo Methods
Module MA5308
This module handbook serves to describe contents, learning outcome, methods and examination type as well as linking to current dates for courses and module examination in the respective sections.
Basic Information
MA5308 is a semester module in English language at Master’s level which is offered irregular.
This module description is valid from SS 2010 to SS 2010.
| Total workload | Contact hours | Credits (ECTS) |
|---|---|---|
| 270 h | 90 h | 9 CP |
Content, Learning Outcome and Preconditions
Content
Introduction to Monte Carlo simulation techniques. Random variable generation. Monte Carlo integration. Markov chain Monte Carlo methods (Metropolis-Hastings algorithm, Gibbs sampler). Diagnosing convergence.
Learning Outcome
At the end of the module students have mathematical understanding of basic Monte Carlo methods, are able to apply Monte Carlo techniques to high-dimensional integration problems and have programming skills for stochastic simulation.
Preconditions
MA1302 Introduction to Numerical Analysis, MA2302 Numerical Analysis, MA1401 Introduction to Probability
Courses, Learning and Teaching Methods and Literature
Courses and Schedule
| Type | SWS | Title | Lecturer(s) | Dates | Links |
|---|---|---|---|---|---|
| VO | 4 | Monte Carlo Methods | |||
| UE | 2 | Monte Carlo Methods (Exercise Session) |
Learning and Teaching Methods
lecture, excercise module, assignments
Media
blackboard
Literature
C. Robert, G. Casella, Monte Carlo Statistical Methods, 2nd Edition, Springer-Verlag, New York, 2004.