Suggests: broom.mixed, haven, knitr, lme4, MASS, metafor, mitml,
miceadds, nnet, pan, randomForest, rmarkdown, rpart, survival,

person("Edoardo", "Costantini", role = "ctb",
person("Caspar", "van Lissa", role = "ctb",
Imports: broom, dplyr, generics, graphics, grDevices, lattice, methods,
Suggests: broom.mixed, decor, glmnet, haven, knitr, lme4, lmtest, MASS,
metafor, mitml, miceadds, nnet, pan, randomForest, ranger,

person("Hanne", "Oberman", role = "ctb",
Suggests: broom.mixed, decor, future, furrr, glmnet, haven, knitr,
lme4, lmtest, MASS, metafor, mitml, miceadds, nnet, pan,
parallelly, purrr, randomForest, ranger, rmarkdown, rpart,

randomForest, Zelig, BSDA, knitr, rmarkdown, testthat, HSAUR3,

Suggests: AGD, gamlss, lme4, mitools, nlme, pan, randomForest, Zelig,
BSDA, knitr, rmarkdown, testthat, HSAUR3, micemd, miceadds,

Imports: broom, dplyr, graphics, lattice, methods, stats, tidyr, utils
Suggests: knitr, lme4, MASS, mitml, miceadds, nnet, pan, randomForest,

rmarkdown, rpart, survival, testthat, lmtest

person("Tobias", "Schumacher", email = "tobias.schumacher1@rwth-aachen.de", role = c("aut", "cre")),
person("Philipp", "Gaffert", email = "philipp.gaffert@gfk.com", role = "aut"),
person("Stef", "van Buuren", email = "stef.vanbuuren at tno.nl", role = "ctb"),
person("Karin", "Groothuis-Oudshoorn", role = "ctb", email = "c.g.m.oudshoorn@utwente.nl"))
Description: Extends and builds on the 'mice' package by
adding a functionality to perform multivariate predictive mean matching on
imputed data as well as new functionalities to perform predictive mean

Title: Fast Imputations Using 'Rcpp' and 'Armadillo'
Fast imputations under the object-oriented programming paradigm.
There was used quantitative models with a closed-form solution. Thus package is based on linear algebra operations.
The biggest improvement in time performance could be achieve for a calculation where a grouping variable have to be used.
Suggests: knitr, rmarkdown, pacman, testthat, mice, dplyr, broom

A single evaluation of a quantitative model for the multiple imputations is another major enhancement.
Suggests: knitr, rmarkdown, pacman, testthat, mice, dplyr, broom, car