superMICE: SuperLearner Method for MICE

Adds a Super Learner ensemble model method (using the 'SuperLearner' package) to the 'mice' package. Laqueur, H. S., Shev, A. B., Kagawa, R. M. C. (2021) <doi:10.1093/aje/kwab271>.

Version: 1.1.1
Imports: stats, mice, SuperLearner
Suggests: arm, bartMachine, class, e1071, earth, extraTrees, gbm, glmnet, ipred, KernelKnn, kernlab, LogicReg, MASS, nnet, party, polspline, randomForest, ranger, rpart, speedglm, spls, xgboost
Published: 2022-05-04
Author: Aaron B. Shev
Maintainer: Aaron B. Shev <abshev at ucdavis.edu>
License: GPL-3
NeedsCompilation: no
Materials: README
CRAN checks: superMICE results

Documentation:

Reference manual: superMICE.pdf

Downloads:

Package source: superMICE_1.1.1.tar.gz
Windows binaries: r-devel: superMICE_1.1.1.zip, r-release: superMICE_1.1.1.zip, r-oldrel: superMICE_1.1.1.zip
macOS binaries: r-release (arm64): superMICE_1.1.1.tgz, r-oldrel (arm64): superMICE_1.1.1.tgz, r-release (x86_64): superMICE_1.1.1.tgz, r-oldrel (x86_64): superMICE_1.1.1.tgz
Old sources: superMICE archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=superMICE to link to this page.