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.