News bulletin

A MOOC on Exploratory multivarate data analysis will start the 2nd of March 2020. Click here for more informations and to enroll.

The version 2.0 of Factoshiny allows you to perform with a unique function (the function Factoshiny) lots of multivariate methods. The function handle missing values, allows to modify the graph interactively and propose an automatic interpretation of the results.

The version 2.0 of FactoMineR plots graphs with ggplot.

The new package FactoInvestigate describes and interprets automatically the results of your principal component analysis (PCA, CA or MCA), choosing the best graphs to show. You just have to write Investigate(res.pca) to obtain the following report on the PCA results of the decathlon example.

A MOOC (Massive Open Online Courses) will start in March 2018. See here the MOOC played in 2017.

Reviews on the book Exploratory Multivariate Analysis by Example using R.

A new package Factoshiny is available on CRAN. It allows us to perform principal component method with a menu and to draw interactive graphs.

New Graphical User Interface in the package RcmdrPlugin.FactoMineR

Vidéos

Videos on the use of FactoMineR (for PCA, multiple factor analysis, clustering, etc.)

A new useR group to ask questions on FactoMineR and on Exploratory Multivariate Data Analysis has been created. Join this group to have news about FactoMineR and to ask questions

missMDA: a new package to handle missing values in PCA, MCA or MFA with FactoMineR

The MFA function (version 1.16 and more) allows you to take into account quantitative groups of variables and/or qualitative groups of variables and/or contingency tables

A description of FactoMineR is available in "FactoMineR: an R package for multivariate analysis", Journal of Statistical Software.