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 Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=miceFast to link to this page.
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