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depscope/conda/r-factominer

r-factominer

condav2.14

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).

License GPL-2.0-or-later20 versions1 maintainers0 deps1,203 weekly dl
husson/FactoMineR
70
/ 100
Health
safe to use

[email protected] is safe to use (health: 70/100)

Health breakdown0 – 100
25/25
maintenance
6/20
popularity
25/25
security
12/15
maturity
2/15
community
Vulnerabilities
0
none known

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First published · 2020-12-11 15:38:06.397000+00:00

Last updated · 2026-04-10 15:55:36.924000+00:00

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