4.00 credits
15.0 h + 7.5 h
Q1
Teacher(s)
Legrand Catherine;
Language
French
Prerequisites
Concepts and tools equivalent to those taught in teaching units
| LSTAT2020 | Logiciels et programmation statistique de base |
| LSTAT2120 | Linear models |
| LSTAT2100 | Modèles linéaires généralisés et données discrêtes |
Main themes
- Review of generalised linear models - Dispersion models - Linear mixed models. - Generalised linear mixed models. - Autoregressive models. - Marginal models and generalised estimating equations.
Learning outcomes
At the end of this learning unit, the student is able to : | |
| 1 |
This is a second cycle course giving a critical overview of recent scientific developments in the field. It will deal with present extensions of linear and generalised linear models. The considered extensions will be of two types : - a explicit modelling of dispersion as a function of available covariates. - a amendment of (generalised) linear models to deal with clustered or longitudinal data. |
Bibliography
Transparents du cours disponible sur Moodle.
Références données au cours.
Références données au cours.
Teaching materials
- transparents sur moodle
Faculty or entity
LSBA
Programmes / formations proposant cette unité d'enseignement (UE)
Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Master [120] in Data Science : Statistic
Master [120] in Biomedical Engineering
Master [120] in Statistics: Biostatistics
Master [120] in Statistics: General
Certificat d'université : Statistique et science des données (15/30 crédits)