missMDA: Handling missing values with/in multivariate data analysis (principal component methods)

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

Version: 1.7.3
Depends: R (≥ 3.0.0), FactoMineR (≥ 1.27)
Published: 2014-11-24
Author: Francois Husson, Julie Josse
Maintainer: Francois Husson <husson at agrocampus-ouest.fr>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://www.agrocampus-ouest.fr/math/husson, http://www.agrocampus-ouest.fr/math/josse
NeedsCompilation: no
In views: OfficialStatistics
CRAN checks: missMDA results

Downloads:

Reference manual: missMDA.pdf
Package source: missMDA_1.7.3.tar.gz
Windows binaries: r-devel: missMDA_1.7.3.zip, r-release: missMDA_1.7.3.zip, r-oldrel: missMDA_1.7.3.zip
OS X Snow Leopard binaries: r-release: missMDA_1.7.3.tgz, r-oldrel: missMDA_1.7.3.tgz
OS X Mavericks binaries: r-release: missMDA_1.7.3.tgz
Old sources: missMDA archive

Reverse dependencies:

Reverse suggests: FactoMineR