CRAN/E | miceFast

miceFast

Fast Imputations Using 'Rcpp' and 'Armadillo'

Installation

About

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.

github.com/Polkas/miceFast
System requirements C++11
Bug report File report

Key Metrics

Version 0.8.2
R ≥ 3.6.0
Published 2022-11-17 534 days ago
Needs compilation? yes
License GPL-2
License GPL-3
CRAN checks miceFast results

Downloads

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Maintainer

Maintainer

Maciej Nasinski

nasinski.maciej@gmail.com

Authors

Maciej Nasinski

aut / cre

Material

README
NEWS
Reference manual
Package source

In Views

MissingData

Vignettes

miceFast - Introduction

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

miceFast archive

Depends

R ≥ 3.6.0

Imports

methods
Rcpp ≥ 0.12.12
data.table

Suggests

knitr
rmarkdown
pacman
testthat
mice
magrittr
ggplot2
UpSetR
dplyr

LinkingTo

Rcpp
RcppArmadillo