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mimi: Main Effects and Interactions in Mixed and Incomplete Data

Generalized low-rank models for mixed and incomplete data frames. The main function may be used for dimensionality reduction of imputation of numeric, binary and count data (simultaneously). Main effects such as column means, group effects, or effects of row-column side information (e.g. user/item attributes in recommendation system) may also be modelled in addition to the low-rank model. Geneviève Robin, Olga Klopp, Julie Josse, Éric Moulines, Robert Tibshirani (2018) <doi:10.48550/arXiv.1806.09734>.

Version: 0.2.0
Depends: R (≥ 2.10)
Imports: glmnet, softImpute, stats, FactoMineR, parallel, doParallel, foreach, data.table, rARPACK
Suggests: knitr, rmarkdown
Published: 2019-03-07
Author: Geneviève Robin
Maintainer: Genevieve Robin <genevieve.robin at polytechnique.edu>
License: GPL-3
NeedsCompilation: no
In views: MissingData
CRAN checks: mimi results

Documentation:

Reference manual: mimi.pdf

Downloads:

Package source: mimi_0.2.0.tar.gz
Windows binaries: r-devel: mimi_0.2.0.zip, r-release: mimi_0.2.0.zip, r-oldrel: mimi_0.2.0.zip
macOS binaries: r-release (arm64): mimi_0.2.0.tgz, r-oldrel (arm64): mimi_0.2.0.tgz, r-release (x86_64): mimi_0.2.0.tgz, r-oldrel (x86_64): mimi_0.2.0.tgz
Old sources: mimi archive

Linking:

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These binaries (installable software) and packages are in development.
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