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A correlation-based batch process for fast, accurate imputation for high dimensional missing data problems via chained random forests. See Waggoner (2023) <doi:10.1007/s00180-023-01325-9> for more on 'hdImpute', Stekhoven and Bühlmann (2012) <doi:10.1093/bioinformatics/btr597> for more on 'missForest', and Mayer (2022) <https://github.com/mayer79/missRanger> for more on 'missRanger'.
| Version: | 0.2.1 |
| Imports: | missRanger, plyr, purrr, magrittr, tibble, dplyr, tidyselect, tidyr, cli |
| Suggests: | testthat (≥ 3.0.0), knitr, rmarkdown, usethis, missForest, tidyverse |
| Published: | 2023-08-07 |
| Author: | Philip Waggoner [aut, cre] |
| Maintainer: | Philip Waggoner <philip.waggoner at gmail.com> |
| BugReports: | https://github.com/pdwaggoner/hdImpute/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/pdwaggoner/hdImpute |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | hdImpute results |
| Reference manual: | hdImpute.pdf |
| Vignettes: |
Getting Started MAD Evaluation NA Checking |
| Package source: | hdImpute_0.2.1.tar.gz |
| Windows binaries: | r-devel: hdImpute_0.2.1.zip, r-release: hdImpute_0.2.1.zip, r-oldrel: hdImpute_0.2.1.zip |
| macOS binaries: | r-release (arm64): hdImpute_0.2.1.tgz, r-oldrel (arm64): hdImpute_0.2.1.tgz, r-release (x86_64): hdImpute_0.2.1.tgz, r-oldrel (x86_64): hdImpute_0.2.1.tgz |
| Old sources: | hdImpute archive |
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