The objectives of this course are to understand the concepts and
statistical methods of multivariate analysis, and to apply them to real
data sets by means of the computer program R.
The course covers the topics
- Multivariate distributions (normal, Whishart, T2, t)
- Multivariate tests (Hotelling's T2, MANOVA, Box's M, some others)
- Discriminant Analysis (LDA, QDA)
- Cluster analysis (k-means, hierarchical clustering, PAM)
- Factor Analysis and Principal Componant Analysis
As a by-product, the course covers other topics partially like likelihood estimation, correlation estimation, bootstrap, EM algorithm, etc.
The seminar is part of the course.
- Enseignant: Marc-Olivier Boldi