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 |
| DOI: | 10.32614/CRAN.package.hdImpute |
| Author: | Philip Waggoner [aut, cre] |
| Maintainer: | Philip Waggoner <philip.waggoner at gmail.com> |
| BugReports: | https://github.com/pdwaggoner/hdImpute/issues |
| License: | MIT + fileLICENSE |
| URL: | https://github.com/pdwaggoner/hdImpute |
| NeedsCompilation: | no |
| Materials: | README,NEWS |
| CRAN checks: | hdImpute results |
| Reference manual: | hdImpute.html ,hdImpute.pdf |
| Vignettes: | Getting Started (source,R code) MAD Evaluation (source,R code) NA Checking (source,R code) |
| 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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