Probability and mathematical statistics [ LSTAT3100 ]
6.0 crédits ECTS
30.0 h
1q
| Teacher(s) |
Segers Johan ;
Van Keilegom Ingrid ;
|
| Language |
English
|
Place
of the course |
Louvain-la-Neuve
|
| Main themes |
The course covers the asymptotic theory in parametric inference, M- and Z- estimators, U-statistics, empirical processes and the functional delta method. In a second part of the course, these tools are applied in modern special topics of mathematical statistics such as, e.g., extreme value theory, ill-posed inverse problems,
|
| Aims |
This course covers the necessary tools in asymptotic statistics in order to perform modern research in statistics.
|
| Content |
Contents
1. Stochastic convergence
2. Delta method and moment estimators
3. Projections and U-statistics
4. Empirical processes
5. M- and Z-estimators
6. Capita selecta on a modern research topic in statistics
Methods
Lectures
Take-home readings
Oral presentations by students
|
| Other information |
Prerequisites:
Analyse statistique (MATH2440)
Evaluation:
Oral presentations during the semester, and oral or written exam covering the lectures.
Support:
A syllabus and/or transparencies.
Supplementary literature:
Serfling, R. J. (1980) Approximation Theorems of Mathematical Statistics. Wiley, New York.
van der Vaart, A. (1998) Asymptotic Statistics. Cambridge University Press, Cambridge.
|
Cycle et année
d'étude |
> Master [120] in Statistics: General
> Certificat universitaire en statistique
|
Faculty or entity
in charge |
> LSBA
|
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|
