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: | 0.6.2 |
| Depends: | R (≥ 3.6.0) |
| Imports: | methods, data.table, dplyr, magrittr, Rcpp (≥ 0.12.12), lifecycle |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | knitr, rmarkdown, pacman, testthat, mice, broom, car, ggplot2 |
| Published: | 2020-07-10 |
| 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: | NEWS |
| In views: | MissingData |
| CRAN checks: | miceFast results |
| Reference manual: | miceFast.pdf |
| Vignettes: |
miceFast - Introduction |
| Package source: | miceFast_0.6.2.tar.gz |
| Windows binaries: | r-devel: miceFast_0.6.2.zip, r-release: miceFast_0.6.2.zip, r-oldrel: miceFast_0.6.2.zip |
| macOS binaries: | r-release: miceFast_0.6.2.tgz, r-oldrel: miceFast_0.6.2.tgz |
| Old sources: | miceFast archive |
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