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deepImp: Imputation with Deep Learning Methods

Imputation of mixed-type and compositional data with neural networks. The architecture (number and size of hidden layers, dropout, activation, optimiser) is user-configurable. See Templ (2021) <doi:10.1007/978-3-030-71175-7>.

Version: 1.1.0
Depends: R (≥ 4.1)
Imports: torch, luz, VIM, robCompositions, stats, utils, graphics
Suggests: keras3, knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2026-06-10
DOI: 10.32614/CRAN.package.deepImp
Author: Matthias Templ ORCID iD [aut, cre]
Maintainer: Matthias Templ <matthias.templ at gmail.com>
License: GPL-2
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: deepImp results

Documentation:

Reference manual: deepImp.html , deepImp.pdf
Vignettes: Neural-network imputation with deepImp (source)

Downloads:

Package source: deepImp_1.1.0.tar.gz
Windows binaries: r-devel: deepImp_1.1.0.zip, r-release: deepImp_1.1.0.zip, r-oldrel: deepImp_1.1.0.zip
macOS binaries: r-release (arm64): deepImp_1.1.0.tgz, r-oldrel (arm64): deepImp_1.1.0.tgz, r-release (x86_64): deepImp_1.1.0.tgz, r-oldrel (x86_64): deepImp_1.1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=deepImp 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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