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RfEmpImp  

Multiple Imputation using Chained Random Forests
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("RfEmpImp", "2.1.8")



Attach the package and use:
library("RfEmpImp")
Maintained by
Shangzhi Hong
[Scholar Profile | Author Map]
First Published: 2020-05-16
Latest Update: 2022-10-20
Description:
An R package for multiple imputation using chained random forests. Implemented methods can handle missing data in mixed types of variables by using prediction-based or node-based conditional distributions constructed using random forests. For prediction-based imputation, the method based on the empirical distribution of out-of-bag prediction errors of random forests and the method based on normality assumption for prediction errors of random forests are provided for imputing continuous variables. And the method based on predicted probabilities is provided for imputing categorical variables. For node-based imputation, the method based on the conditional distribution formed by the predicting nodes of random forests, and the method based on proximity measures of random forests are provided. More details of the statistical methods can be found in Hong et al. (2020) .
How to cite:
Shangzhi Hong (2020). RfEmpImp: Multiple Imputation using Chained Random Forests. R package version 2.1.8, https://cran.r-project.org/web/packages/RfEmpImp. Accessed 10 May. 2025.
Previous versions and publish date:
2.0.3 (2020-05-16 11:30), 2.1.5 (2020-06-25 07:00)
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Complete documentation for RfEmpImp
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