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literanger
View on CRAN: Click
here
Download and install literanger package within the R console
Install from CRAN:
install.packages("literanger")
Install from Github:
library("remotes")
install_github("cran/literanger")
Install by package version:
library("remotes")
install_version("literanger", "0.1.1")
Attach the package and use:
library("literanger")
Maintained by
Stephen Wade
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-06-26
Latest Update: 2023-07-13
Description:
An updated implementation of R package 'ranger' by Wright et al,
(2017) for training and predicting from random
forests, particularly suited to high-dimensional data, and for embedding in
'Multiple Imputation by Chained Equations' (MICE) by van Buuren (2007)
. Ensembles of classification and regression
trees are currently supported. Sparse data of class 'dgCMatrix' (R package
'Matrix') can be directly analyzed. Conventional bagged predictions are
available alongside an efficient prediction for MICE via the algorithm
proposed by Doove et al (2014) . Survival
and probability forests are not supported in the update, nor is data of
class 'gwaa.data' (R package 'GenABEL'); use the original 'ranger' package
for these analyses.
How to cite:
Stephen Wade (2023). literanger: Random Forests for Multiple Imputation Based on 'ranger'. R package version 0.1.1, https://cran.r-project.org/web/packages/literanger. Accessed 22 Dec. 2024.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for literanger
Functions, R codes and Examples using
the literanger R package
Some associated functions: literanger-package . predict.literanger . train .
Some associated R codes: cpp11.R . literanger-package.R . predict.R . train.R . utility.R . Full literanger package functions and examples
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