Package: mixgb 1.4.2

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>. Our method utilizes the capabilities of XGBoost, a highly efficient implementation of gradient boosted trees, to capture interactions and non-linear relations automatically. Moreover, we have integrated subsampling and predictive mean matching to minimize bias and reflect appropriate imputation variability. This package supports various types of variables and offers flexible settings for subsampling and predictive mean matching. Additionally, it includes diagnostic tools for evaluating the quality of the imputed values.

Authors:Yongshi Deng [aut, cre], Thomas Lumley [ths]

mixgb_1.4.2.tar.gz
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mixgb.pdf |mixgb.html✨
mixgb/json (API)

# Install 'mixgb' in R:
install.packages('mixgb', repos = c('https://agnesdeng.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/agnesdeng/mixgb/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • nhanes3 - A small subset of the NHANES III (1988-1994) newborn data
  • nhanes3_newborn - NHANES III (1988-1994) newborn data

On CRAN:

17 exports 21 stars 2.43 score 79 dependencies 88 scripts 318 downloads

Last updated 8 months agofrom:6e1b3c62b6. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 05 2024
R-4.5-win-x86_64NOTESep 05 2024
R-4.5-linux-x86_64NOTESep 05 2024
R-4.4-win-x86_64NOTESep 05 2024
R-4.4-mac-x86_64NOTESep 05 2024
R-4.4-mac-aarch64NOTESep 05 2024
R-4.3-win-x86_64NOTESep 05 2024
R-4.3-mac-x86_64NOTESep 05 2024
R-4.3-mac-aarch64NOTESep 05 2024

Exports:createNAdata_cleandefault_paramsdefault_params_cranimpute_newmixgbmixgb_cvmixgb0plot_1num1facplot_1num2facplot_2facplot_2numplot_2num1facplot_barplot_boxplot_histshow_var

Dependencies:backportsbitbit64bootbroomclicliprcodetoolscolorspacecpp11crayondata.tabledplyrfansifarverforcatsforeachgenericsggplot2glmnetgluegtablehavenhmsisobanditeratorsjomojsonlitelabelinglatticelifecyclelme4magrittrMASSMatrixmgcvmiceminqamitmlmunsellnlmenloptrnnetnumDerivordinalpanpillarpkgconfigprettyunitsprogresspurrrR6RColorBrewerRcppRcppArmadilloRcppEigenRcppGSLRcppParallelRcppZigguratreadrRfastrlangrpartscalesshapestringistringrsurvivaltibbletidyrtidyselecttzdbucminfutf8vctrsviridisLitevroomwithrxgboost

Imputing newdata with a saved mixgb imputer

Yongshi Deng

Rendered fromImputing-newdata.Rmdusingknitr::rmarkdownon Sep 05 2024.

Last update: 2023-11-27
Started: 2022-05-18

mixgb: Multiple Imputation Through XGBoost

Yongshi Deng

Rendered fromUsing-mixgb.Rmdusingknitr::rmarkdownon Sep 05 2024.

Last update: 2023-03-14
Started: 2022-05-18