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MixRF: A Random-Forest-Based Approach for Imputing Clustered Incomplete Data

It offers random-forest-based functions to impute clustered incomplete data. The package is tailored for but not limited to imputing multitissue expression data, in which a gene's expression is measured on the collected tissues of an individual but missing on the uncollected tissues.

Version: 1.0
Depends: doParallel, randomForest, lme4, foreach
Published: 2016-04-06
DOI: 10.32614/CRAN.package.MixRF
Author: Jiebiao Wang and Lin S. Chen
Maintainer: Jiebiao Wang <randel.wang at gmail.com>
BugReports: https://github.com/randel/MixRF/issues
License: GPL-2 | GPL-3 [expanded from: GPL]
URL: https://github.com/randel/MixRF
NeedsCompilation: no
CRAN checks: MixRF results

Documentation:

Reference manual: MixRF.pdf

Downloads:

Package source: MixRF_1.0.tar.gz
Windows binaries: r-devel: MixRF_1.0.zip, r-release: MixRF_1.0.zip, r-oldrel: MixRF_1.0.zip
macOS binaries: r-release (arm64): MixRF_1.0.tgz, r-oldrel (arm64): MixRF_1.0.tgz, r-release (x86_64): MixRF_1.0.tgz, r-oldrel (x86_64): MixRF_1.0.tgz

Linking:

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