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missMDA: Handling Missing Values with Multivariate Data Analysis

Imputation of incomplete continuous or categorical datasets; Missing values are imputed with a principal component analysis (PCA), a multiple correspondence analysis (MCA) model or a multiple factor analysis (MFA) model; Perform multiple imputation with and in PCA or MCA.

Version: 1.19
Depends: R (≥ 4.0)
Imports: FactoMineR (≥ 2.3), ggplot2, graphics, grDevices, mice, mvtnorm, stats, utils, doParallel, parallel, foreach
Suggests: knitr, markdown
Published: 2023-11-17
DOI: 10.32614/CRAN.package.missMDA
Author: Francois Husson, Julie Josse
Maintainer: Francois Husson <francois.husson at institut-agro.fr>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://factominer.free.fr/missMDA/index.html
NeedsCompilation: no
Citation: missMDA citation info
Materials: README
In views: MissingData, Psychometrics
CRAN checks: missMDA results

Documentation:

Reference manual: missMDA.pdf
Vignettes: MulitpleImputation
missMDA

Downloads:

Package source: missMDA_1.19.tar.gz
Windows binaries: r-devel: missMDA_1.19.zip, r-release: missMDA_1.19.zip, r-oldrel: missMDA_1.19.zip
macOS binaries: r-release (arm64): missMDA_1.19.tgz, r-oldrel (arm64): missMDA_1.19.tgz, r-release (x86_64): missMDA_1.19.tgz, r-oldrel (x86_64): missMDA_1.19.tgz
Old sources: missMDA archive

Reverse dependencies:

Reverse depends: imp4p
Reverse imports: Factoshiny, geneticae, INSPIRE, missCompare, NIMAA, OTrecod
Reverse suggests: clusterMI, denoiseR, FactoMineR, padma

Linking:

Please use the canonical form https://CRAN.R-project.org/package=missMDA to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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