mixgb: Multiple Imputation Through 'XGBoost'
Multiple imputation using 'XGBoost', subsampling, and predictive mean
matching as described in Deng and Lumley (2024)
<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: |
2.2.3 |
| Depends: |
R (≥ 4.3.0) |
| Imports: |
cli, data.table, Matrix, mice, Rcpp, Rfast, stats, utils, xgboost (≥ 3.1.2.1) |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
knitr, rmarkdown, testthat (≥ 3.0.0) |
| Published: |
2026-01-17 |
| DOI: |
10.32614/CRAN.package.mixgb |
| Author: |
Yongshi Deng
[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 |
| SystemRequirements: |
macOS: Accelerate framework |
| Language: |
en-GB |
| Citation: |
mixgb citation info |
| Materials: |
NEWS |
| CRAN checks: |
mixgb results |
Documentation:
Downloads:
Reverse dependencies:
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