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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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