Package: miceFast
Title: Fast Imputations Using 'Rcpp' and 'Armadillo'
Version: 0.8.1
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, Rcpp (>= 0.12.12), data.table
Suggests: knitr, rmarkdown, pacman, testthat, mice, magrittr, ggplot2,
        UpSetR, dplyr
VignetteBuilder: knitr
LinkingTo: Rcpp, RcppArmadillo
RcppModules: miceFast, corrData
SystemRequirements: C++11
NeedsCompilation: yes
LazyData: true
RoxygenNote: 7.1.2
Packaged: 2022-03-13 23:52:26 UTC; maciejnasinski
Author: Maciej Nasinski [aut, cre]
Maintainer: Maciej Nasinski <nasinski.maciej@gmail.com>
Repository: CRAN
Date/Publication: 2022-03-14 00:10:02 UTC
Built: R 4.0.5; x86_64-apple-darwin17.0; 2022-03-14 10:29:58 UTC; unix
Archs: miceFast.so.dSYM
