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miceFast  

Fast Imputations Using 'Rcpp' and 'Armadillo'
View on CRAN: Click here


Download and install miceFast package within the R console
Install from CRAN:
install.packages("miceFast")

Install from Github:
library("remotes")
install_github("cran/miceFast")

Install by package version:
library("remotes")
install_version("miceFast", "0.8.2")



Attach the package and use:
library("miceFast")
Maintained by
Maciej Nasinski
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-03-19
Latest Update: 2022-11-17
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.
How to cite:
Maciej Nasinski (2018). miceFast: Fast Imputations Using 'Rcpp' and 'Armadillo'. R package version 0.8.2, https://cran.r-project.org/web/packages/miceFast. Accessed 21 Nov. 2024.
Previous versions and publish date:
0.0.1 (2018-03-19 12:34), 0.0.2 (2018-03-25 17:30), 0.1.0 (2018-04-16 19:58), 0.2.3 (2018-05-06 22:19), 0.5.1 (2019-08-20 00:50), 0.6.1 (2020-07-07 00:00), 0.6.2 (2020-07-10 17:20), 0.6.9 (2020-12-13 16:50), 0.7.1 (2021-07-10 20:40), 0.8.1 (2022-03-14 01:10)
Other packages that cited miceFast R package
View miceFast citation profile
Other R packages that miceFast depends, imports, suggests or enhances
Complete documentation for miceFast
Functions, R codes and Examples using the miceFast R package
Some associated functions: Rcpp_corrData-class . Rcpp_miceFast-class . VIF . air_miss . compare_imp . fill_NA . fill_NA_N . miceFast-package . naive_fill_NA . neibo . upset_NA . 
Some associated R codes: RcppExports.R . VIF.R . data.R . fill_NA.R . fill_NA_N.R . naive_fill_NA.R . plots.R . zzz.R .  Full miceFast package functions and examples
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