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.
knitr, rmarkdown, pacman, testthat, mice, dplyr, broom

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

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.
A single evaluation of a quantitative model for the multiple imputations is another major enhancement.
Moreover there are offered a few functions built to work with popular R packages such as 'data.table'.
data.table, knitr, rmarkdown, pacman, testthat, mice, dplyr,
broom, car, magrittr

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.
A single evaluation of a quantitative model for the multiple imputations is another major enhancement.
Moreover there are offered a few functions built to work with popular R packages such as 'data.table' or 'dplyr'.
dplyr, knitr, rmarkdown, pacman, testthat, mice, broom, car,
magrittr, ggplot2