Package: missCforest 0.0.8

missCforest: Ensemble Conditional Trees for Missing Data Imputation

Single imputation based on the Ensemble Conditional Trees (i.e. Cforest algorithm Strobl, C., Boulesteix, A. L., Zeileis, A., & Hothorn, T. (2007) <doi:10.1186/1471-2105-8-25>).

Authors:Imad El Badisy [aut, cre], Roch Giorgi [ctb]

missCforest_0.0.8.tar.gz
missCforest_0.0.8.zip(r-4.7)missCforest_0.0.8.zip(r-4.6)missCforest_0.0.8.zip(r-4.5)
missCforest_0.0.8.tgz(r-4.6-any)missCforest_0.0.8.tgz(r-4.5-any)
missCforest_0.0.8.tar.gz(r-4.7-any)missCforest_0.0.8.tar.gz(r-4.6-any)
missCforest_0.0.8.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
missCforest/json (API)

# Install 'missCforest' in R:

install.packages('missCforest', repos = c('https://ielbadisy.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ielbadisy/misscforest/issues

On CRAN:

2.70 score 4 scripts 227 downloads 2 exports 9 dependencies

Last updated from:0fb40f77e5. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	127
source / vignettes	OK	154
linux-release-x86_64	OK	127
macos-release-arm64	OK	133
macos-oldrel-arm64	OK	75
windows-devel	OK	133
windows-release	OK	73
windows-oldrel	OK	79
wasm-release	OK	98