The function 'missForest' in this package is used to impute missing values particularly in the case of mixed-type data. It uses a random forest trained on the observed values of a data matrix to predict the missing values. It can be used to impute continuous and/or categorical data including complex interactions and non-linear relations. It yields an out-of-bag (OOB) imputation error estimate without the need of a test set or elaborate cross-validation. It can be run in parallel to save computation time.
| Version: | 1.4 |
| Depends: | randomForest, foreach, itertools |
| Published: | 2013-12-31 |
| Author: | Daniel J. Stekhoven |
| Maintainer: | Daniel J. Stekhoven <stekhoven at stat.math.ethz.ch> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | http://www.r-project.org, https://github.com/stekhoven/missForest |
| NeedsCompilation: | no |
| Citation: | missForest citation info |
| Materials: | README |
| In views: | MissingData, OfficialStatistics |
| CRAN checks: | missForest results |
| Reference manual: | missForest.pdf |
| Package source: | missForest_1.4.tar.gz |
| Windows binaries: | r-devel: missForest_1.4.zip, r-release: missForest_1.4.zip, r-oldrel: missForest_1.4.zip |
| macOS binaries: | r-release: missForest_1.4.tgz, r-oldrel: missForest_1.4.tgz |
| Old sources: | missForest archive |
| Reverse depends: | bartMachine, imp4p |
| Reverse imports: | ADAPTS, KarsTS, obliqueRSF, pmp, proFIA, smartdata, speaq |
| Reverse suggests: | CBDA, simputation, tidyLPA |
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