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: | 0.8.5 |
| 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: | 2025-02-03 |
| 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 |
| Materials: | README,NEWS |
| In views: | MissingData |
| CRAN checks: | miceFast results |
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