An introduction to graph analysis and modeling
This repository regroups the material (slides, practicals, projects) associated to the course about “graph analysis and modeling”, as a part of the MSc in Statistics for Smart Data.
Descriptive Analysis of Network Data
November the 6th, 2018
- Course Statistics on network data, Graph Partitionning - slides
- Tutorial Basical graph manipulation and Spectral Clustering sheet
Statistical Models for Networks Data: SBM part 1
November the 15th, 2018
Statistical Models for Networks Data: SBM part 2
- Course: Variational EM algorithm, Stochastic Block Model - slides
- Tutorial: Stochastic Block Model and variational inference sheet
November the 22th, 2018
Basic packages for R extensions
install.packages("devtools") install.packages("knitr") install.packages("rmarkdown") install.packages("aricode") install.packages("Matrix")
Packages for graph manipulation
install.packages("igraph") install.packages("sna") install.packages("network")
Packages for stochastic block models
install.packages("blockmodels") install.packages("mixer") ## you must install from source
Packages for fancy plotting
Evaluation and Projects: extension of the stochastic block model
- Projects are here: subjects
Subjects of the projects will be discussed on the 22th of November.
Evaluation of the module will be made based on 1) a report (less than 10 pages in English) and 2) A 15 talks presenting your project and 3) the reports sent at the end of each tutorial.
Some book (not freely available, sorry)
- Statistical Analysis of Network Data: Methods and Models, by Eric D. Kolaczyk
- Statistical Analysis of Network Data with R, by Eric D. Kolaczyk, Gábor Csárdi
- Bishop, C. (2000). Introduction to graphical modelling, 2nd edn. Springer, New York.
- Højsgaard, S., Edwards , D., Lauritzen, S. (2012). Graphical Models with R. Springer, New York.
Some material online