_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-mixgb 2.2.3
Propagated dependencies: r-xgboost@1.7.11.1 r-rfast@2.1.5.2 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-mice@3.18.0 r-matrix@1.7-4 r-data-table@1.17.8 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/agnesdeng/mixgb
Licenses: GPL 3+
Build system: r
Synopsis: Multiple Imputation Through 'XGBoost'
Description:

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.

Total results: 1