Duration
24h Th, 12h Pr, 10h Proj.
Number of credits
| Master in mathematics (120 ECTS) | 8 crédits | |||
| Master in mathematics (60 ECTS) | 8 crédits |
Lecturer
N..., Yvik Swan
Coordinator
Language(s) of instruction
English language
Organisation and examination
Teaching in the second semester
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
1 Introduction
2 Models and challenges
3 Generating random variables
4 Generating random processes
5 Monte Carlo Integration and Optimization
6 Markov Chain Monte Carlo
7 Statistical analysis of simulation data
8 Variance reduction
Learning outcomes of the learning unit
Good understanding of the problematics related to simulation and sampling.
Prerequisite knowledge and skills
To follow this course it is mandatory to have solid foundations in
- probability theory (probability measure, probability distributions both uni and multi-variate, CLT, Law of large numbers, ...)
- parametric statistics (likelihood, fisher information, statistical tests, confidence intervals, ...)
Reference for the basics : Casella, George, and Roger L. Berger. Statistical inference. Vol. 2. Pacific Grove, CA: Duxbury, 2002.
Planned learning activities and teaching methods
Ex cathedra teaching, exercise sessions (both on computer and on paper). An end of term assignement is planned, though the precise modalities still need to be fixed.
Mode of delivery (face-to-face ; distance-learning)
face-to-face
Recommended or required readings
All information (course notes, project and exercise sheets) will be made available via the eCampus platform.
Références
Kroese, Dirk P., Thomas Taimre, and Zdravko I. Botev. Handbook of monte carlo methods. Vol. 706. John Wiley & Sons, 2013.
Robert, Christian, and George Casella. Monte Carlo statistical methods. Springer Science & Business Media, 2013.
Robert, Christian P., George Casella, and George Casella. Introducing monte carlo methods with r. Vol. 18. New York: Springer, 2010.
Assessment methods and criteria
To be determined in terms of the project. Precise information will be communicated at the beginning of the course.
Work placement(s)
Organizational remarks
Contacts
Yvik Swan
Office : B37 0/68
Phone : +32 4 366 94 76
Email : yswan at ulg.ac.be