CRAN/E | miceRanger

miceRanger

Multiple Imputation by Chained Equations with Random Forests

Installation

About

Multiple Imputation has been shown to be a flexible method to impute missing values by Van Buuren (2007) doi:10.1177/0962280206074463. Expanding on this, random forests have been shown to be an accurate model by Stekhoven and Buhlmann to impute missing values in datasets. They have the added benefits of returning out of bag error and variable importance estimates, as well as being simple to run in parallel.

github.com/FarrellDay/miceRanger
Bug report File report

Key Metrics

Version 1.5.0
R ≥ 3.5.0
Published 2021-09-06 964 days ago
Needs compilation? no
License MIT
License File
CRAN checks miceRanger results

Downloads

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Maintainer

Maintainer

Sam Wilson

samwilson303@gmail.com

Authors

Sam Wilson

aut / cre

Material

NEWS
Reference manual
Package source

In Views

MissingData

Vignettes

Diagnostic Plotting
The MICE Algorithm
Filling in Missing Data with miceRanger

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

miceRanger archive

Depends

R ≥ 3.5.0

Imports

ranger
data.table
stats
FNN
ggplot2
crayon
corrplot
ggpubr
DescTools
foreach

Suggests

knitr
rmarkdown
doParallel
testthat ≥ 2.1.0