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mixgb: Multiple Imputation Through 'XGBoost'

Multiple imputation using 'XGBoost', subsampling, and predictive mean matching as described in Deng and Lumley (2023) <doi:10.1080/10618600.2023.2252501>. The package supports various types of variables, offers flexible settings, and enables saving an imputation model to impute new data. Data processing and memory usage have been optimised to speed up the imputation process.

Version: 1.5.2
Depends: R (≥ 3.6.0)
Imports: data.table, Matrix, mice, Rcpp, Rfast, stats, utils, xgboost (≥ 1.7.5.1), magrittr
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown
Published: 2024-12-02
DOI: 10.32614/CRAN.package.mixgb
Author: Yongshi Deng ORCID iD [aut, cre], Thomas Lumley [ths]
Maintainer: Yongshi Deng <agnes.yongshideng at gmail.com>
BugReports: https://github.com/agnesdeng/mixgb/issues
License: GPL (≥ 3)
URL: https://github.com/agnesdeng/mixgb
NeedsCompilation: yes
Citation: mixgb citation info
Materials: NEWS
CRAN checks: mixgb results

Documentation:

Reference manual: mixgb.pdf
Vignettes: Imputing newdata with a saved mixgb imputer (source, R code)
mixgb: Multiple Imputation Through XGBoost (source, R code)

Downloads:

Package source: mixgb_1.5.2.tar.gz
Windows binaries: r-devel: mixgb_1.5.2.zip, r-release: mixgb_1.5.2.zip, r-oldrel: mixgb_1.5.2.zip
macOS binaries: r-release (arm64): mixgb_1.5.2.tgz, r-oldrel (arm64): mixgb_1.5.2.tgz, r-release (x86_64): mixgb_1.5.2.tgz, r-oldrel (x86_64): mixgb_1.5.2.tgz
Old sources: mixgb archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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