Other packages > Find by keyword >

FactoMineR  

Multivariate Exploratory Data Analysis and Data Mining
View on CRAN: Click here


Download and install FactoMineR package within the R console
Install from CRAN:
install.packages("FactoMineR")

Install from Github:
library("remotes")
install_github("cran/FactoMineR")

Install by package version:
library("remotes")
install_version("FactoMineR", "2.13")



Attach the package and use:
library("FactoMineR")
Maintained by
Francois Husson
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2006-04-11
Latest Update: 2025-07-23
Description:
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).
How to cite:
Francois Husson (2006). FactoMineR: Multivariate Exploratory Data Analysis and Data Mining. R package version 2.13, https://cran.r-project.org/web/packages/FactoMineR. Accessed 26 Aug. 2026.
Previous versions and publish date:
1.00 (2006-04-11 17:14), 1.01 (2006-05-31 09:02), 1.02 (2006-09-08 14:24), 1.03 (2007-02-15 13:28), 1.04 (2007-02-26 10:36), 1.05 (2007-04-06 16:21), 1.07 (2007-10-07 10:29), 1.08 (2008-02-22 15:25), 1.09 (2008-07-12 20:11), 1.10 (2008-09-16 09:20), 1.12 (2009-04-26 16:21), 1.14 (2010-05-10 21:27), 1.16 (2011-07-07 10:07), 1.18 (2012-01-27 16:13), 1.19 (2012-06-27 15:25), 1.20 (2012-10-02 08:51), 1.21 (2013-01-14 18:27), 1.23 (2013-02-12 18:08), 1.24 (2013-03-29 18:47), 1.25 (2013-05-09 19:08), 1.26 (2014-04-09 14:02), 1.27 (2014-08-28 09:01), 1.28 (2014-12-12 10:56), 1.29 (2015-02-06 11:10), 1.30 (2015-06-15 19:14), 1.31.2 (2015-07-06 19:00), 1.31.3 (2015-07-09 14:29), 1.31.4 (2015-10-10 00:21), 1.31.5 (2016-01-07 14:13), 1.32 (2016-02-24 15:47), 1.33 (2016-05-18 10:36), 1.34 (2016-11-17 14:34), 1.35 (2017-02-20 15:12), 1.36 (2017-06-15 02:17), 1.38 (2017-10-07 18:20), 1.39 (2017-11-10 12:43), 1.40 (2018-03-28 10:18), 1.41 (2018-05-04 15:19), 1.42 (2019-07-03 12:20), 2.0 (2019-11-25 16:50), 2.1 (2020-01-17 19:20), 2.2 (2020-02-05 18:10), 2.3 (2020-02-29 16:20), 2.4 (2020-12-11 12:40), 2.5 (2022-09-05 19:00), 2.6 (2022-09-09 12:53), 2.7 (2022-12-14 17:50), 2.8 (2023-03-27 10:50), 2.9 (2023-10-13 00:40), 2.10 (2024-02-29 20:52), 2.11 (2024-04-20 10:42), 2.12 (2025-07-23 16:40), 2.13 (2026-01-12 12:50), 2.14 (2026-04-08 12:50), 2.15 (2026-06-11 11:00), (2026-07-09 08:04)
Other packages that cited FactoMineR R package
View FactoMineR citation profile
Other R packages that FactoMineR depends, imports, suggests or enhances
Complete documentation for FactoMineR
Functions, R codes and Examples using the FactoMineR R package
Some associated functions: AovSum . CA . CaGalt . DMFA . FAMD . FactoMineR-package . HCPC . HMFA . JO . LinearModel . MCA . MFA . PCA . RegBest . autoLab . catdes . children . coeffRV . condes . coord.ellipse . decathlon . desfreq . dimdesc . ellipseCA . estim_ncp . footsize . geomorphology . gpa . graph.var . health . hobbies . meansComp . milk . mortality . plot.CA . plot.CaGalt . plot.DMFA . plot.FAMD . plot.GPA . plot.GPApartial . plot.HCPC . plot.HMFA . plot.MCA . plot.MFA . plot.MFApartial . plot.PCA . plot.catdes . plot.meansComp . plotellipses . poison . poison.text . poulet . predict.CA . predict.FAMD . predict.LinearModel . predict.MCA . predict.MFA . predict.PCA . prefpls . print.AovSum . print.CA . print.CaGalt . print.FAMD . print.GPA . print.HCPC . print.HMFA . print.LinearModel . print.MCA . print.MFA . print.PCA . print.catdes . print.condes . reconst . senso . simule . summary.CA . summary.CaGalt . summary.FAMD . summary.MCA . summary.MFA . summary.PCA . svd.triplet . tab.disjonctif . tab.disjonctif.prop . tea . textual . wine . write.infile . 
Some associated R codes: CA.R . CaGalt.R . DMFA.R . FAMD.R . GPA.R . HCPC.R . HMFA.R . LinearModel.R . MCA.R . MFA.R . PCA.R . autoLab.R . coeffRV.R . coord.ellipse.R . descfreq.R . ellipseCA.R . graph.var.R . meansComp.R . plot.CA.R . plot.CaGalt.R . plot.DMFA.R . plot.FAMD.R . plot.GPA.R . plot.HCPC.R . plot.HMFA.R . plot.MCA.R . plot.MFA.R . plot.PCA.R . plot.catdes.R . plot.meansComp.R . plotGPApartial.R . plotMFApartial.R . predict.CA.R . predict.FAMD.R . predict.LinearModel.R . predict.MCA.R . predict.MFA.R . predict.PCA.R . print.AovSum.R . print.CA.R . print.CaGalt.R . print.FAMD.R . print.GPA.R . print.HCPC.R . print.HMFA.R . print.LinearModel.R . print.MCA.R . print.MFA.R . print.PCA.R . print.catdes.R . print.condes.R . print.dimdesc.R . reconst.R . summary.CaGalt.R . svd.triplet.R . tab.disjonctif.R . tab.disjonctif.prop.R . write.infile.R . zz.R .  Full FactoMineR package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

RCytoGPS  
Using Cytogenetics Data in R
Defines classes and methods to process text-based cytogenetics using the CytoGPS web site, then imp ...
Download / Learn more Package Citations See dependency  
PCADSC  
Tools for Principal Component Analysis-Based Data Structure Comparisons
A suite of non-parametric, visual tools for assessing differences in data structures for two datase ...
Download / Learn more Package Citations See dependency  
ncodeR  
Techniques for Automated Classifiers
A set of techniques that can be used to develop, validate, and implement automated classifiers. A po ...
Download / Learn more Package Citations See dependency  
leafgl  
High-Performance 'WebGl' Rendering for Package 'leaflet'
Provides bindings to the 'Leaflet.glify' JavaScript library which extends the 'leaflet' JavaScript l ...
Download / Learn more Package Citations See dependency  
nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  
SelvarMix  
Regularization for Variable Selection in Model-Based Clustering and Discriminant Analysis
Performs a regularization approach to variable selection in themodel-based clustering and classifica ...
Download / Learn more Package Citations See dependency  

28,332

R Packages

239,283

Dependencies

75,113

Author Associations

28,333

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA