FactoMineR
Multivariate Exploratory Data Analysis and Data Mining
Exploratory data analysis methods to summarize, visualize and describe datasets. The main principal component methods are available, those with the largest potential in terms of applications: principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, Multiple Factor Analysis when variables are structured in groups, etc. and hierarchical cluster analysis. F. Husson, S. Le and J. Pages (2017).
- Version2.11
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- FactoMineR citation info
- Last release04/20/2024
Documentation
Team
Francois Husson
Julie Josse
Sebastien Le
Jeremy Mazet
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- Imports13 packages
- Suggests4 packages
- Reverse Depends7 packages
- Reverse Imports43 packages
- Reverse Suggests16 packages