miceFast: Fast Imputations Using 'Rcpp' and 'Armadillo'

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.

Version:	0.8.2
Depends:	R (≥ 3.6.0)
Imports:	methods, Rcpp (≥ 0.12.12), data.table
LinkingTo:	Rcpp, RcppArmadillo
Suggests:	knitr, rmarkdown, pacman, testthat, mice, magrittr, ggplot2, UpSetR, dplyr
Published:	2022-11-17
DOI:	10.32614/CRAN.package.miceFast
Author:	Maciej Nasinski [aut, cre]
Maintainer:	Maciej Nasinski <nasinski.maciej at gmail.com>
BugReports:	https://github.com/Polkas/miceFast/issues
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL:	https://github.com/Polkas/miceFast
NeedsCompilation:	yes
SystemRequirements:	C++11
Materials:	README NEWS
In views:	MissingData
CRAN checks:	miceFast results

Documentation:

Reference manual:	miceFast.pdf
Vignettes:	miceFast - Introduction

Downloads:

Package source:	miceFast_0.8.2.tar.gz
Windows binaries:	r-devel: miceFast_0.8.2.zip, r-release: miceFast_0.8.2.zip, r-oldrel: miceFast_0.8.2.zip
macOS binaries:	r-release (arm64): miceFast_0.8.2.tgz, r-oldrel (arm64): miceFast_0.8.2.tgz, r-release (x86_64): miceFast_0.8.2.tgz, r-oldrel (x86_64): miceFast_0.8.2.tgz
Old sources:	miceFast archive

Linking:

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