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


Reference manual: MixRF.pdf


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


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