Multiple Imputation has been shown to be a flexible method to impute missing values by Van Buuren (2007) <doi:10.1177/0962280206074463>. Expanding on this, random forests have been shown to be an accurate model by Stekhoven and Buhlmann <arXiv:1105.0828> to impute missing values in datasets. They have the added benefits of returning out of bag error and variable importance estimates, as well as being simple to run in parallel.
| Version: | 1.3.5 |
| Depends: | R (≥ 3.5.0) |
| Imports: | ranger, data.table, stats, FNN, ggplot2, crayon, corrplot, ggpubr, DescTools, foreach |
| Suggests: | knitr, rmarkdown, doParallel, testthat (≥ 2.1.0) |
| Published: | 2020-04-03 |
| Author: | Sam Wilson [aut, cre] |
| Maintainer: | Sam Wilson <samwilson303 at gmail.com> |
| BugReports: | https://github.com/FarrellDay/miceRanger/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/FarrellDay/miceRanger |
| NeedsCompilation: | no |
| Materials: | NEWS |
| In views: | MissingData |
| CRAN checks: | miceRanger results |
| Reference manual: | miceRanger.pdf |
| Vignettes: |
Diagnostic Plotting The MICE Algorithm Filling in Missing Data with miceRanger |
| Package source: | miceRanger_1.3.5.tar.gz |
| Windows binaries: | r-devel: miceRanger_1.3.5.zip, r-release: miceRanger_1.3.5.zip, r-oldrel: miceRanger_1.3.5.zip |
| macOS binaries: | r-release: miceRanger_1.3.5.tgz, r-oldrel: miceRanger_1.3.5.tgz |
| Old sources: | miceRanger archive |
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