Individual Electricity Consumers

Data, Packages and Methods

19 - 20 October, Paris Saclay


Datasets are made available in the packages below.


You will need a working R environment (version 3.4.2 Short Summer) for the GAM course. An integrated development environment like Rstudio is useful.

For the cours, some additional package must also be installed. For your convenince you may copy and paste the lines below.

Please install all the packages before the course. The estimated installation time is less than 10 minutes if there is no problem.

install.packages(c("devtools", "qgam", "e1071", "gamair"))

Vignette of mgcViz package
Vignette of qgam package


Slides for the course

  1. Generalized Additive Models
  2. More basis penalty smoothers
  3. Smooth additive models for large datasets
  4. Additive quantile regression with an illustration on how to use qgam
  5. mgcViz: scalable visualizations for GAMs


  1. Exercises morning (Solution)
  2. Exercises afternoon I and the solutions
  3. Exercises afternoon II and the solutions