Package: miceFast
Title: Fast Imputations Using 'Rcpp' and 'Armadillo'
Version: 0.6.9
Authors@R: person("Maciej", "Nasinski", email = "nasinski.maciej@gmail.com", role = c("aut", "cre"))
Description: 
  Fast imputations under the object-oriented programming paradigm. 	
  Moreover there are offered a few functions built to work with popular R packages such as 'data.table' or 'dplyr'.
	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.
	A new major improvement is one of the fastest predictive mean matching in the R world because of presorting and binary search.
Depends: R (>= 3.6.0)
License: GPL (>= 2)
URL: https://github.com/Polkas/miceFast
BugReports: https://github.com/Polkas/miceFast/issues
Encoding: UTF-8
Imports: methods, data.table, dplyr, magrittr, Rcpp (>= 0.12.12),
        UpSetR, ggplot2, tidyr, assertthat
Suggests: knitr, rmarkdown, pacman, testthat, mice, broom, car
VignetteBuilder: knitr
LinkingTo: Rcpp, RcppArmadillo
RcppModules: miceFast,corrData
SystemRequirements: C++11
NeedsCompilation: yes
LazyData: true
RoxygenNote: 7.1.1
Packaged: 2020-12-13 15:08:17 UTC; maciejnasinski
Author: Maciej Nasinski [aut, cre]
Maintainer: Maciej Nasinski <nasinski.maciej@gmail.com>
Repository: CRAN
Date/Publication: 2020-12-13 15:50:02 UTC
Built: R 3.6.3; x86_64-w64-mingw32; 2021-05-12 22:07:12 UTC; windows
Archs: i386, x64
