CRAN/E | RfEmpImp

RfEmpImp

Multiple Imputation using Chained Random Forests

Installation

About

An R package for methods of multiple imputation using chained random forests. Implemented methods can handle missing data in mixed types of 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 are provided for continuous variables. And the method based on predicted probabilities is provided for 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) .

Citation RfEmpImp citation info
github.com/shangzhi-hong/RfEmpImp
Bug report File report

Key Metrics

Version 2.1.5
R ≥ 3.5.0
Published 2020-06-25 1449 days ago
Needs compilation? no
License GPL-3
CRAN checks RfEmpImp results

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Maintainer

Maintainer

Shangzhi Hong

Authors

Shangzhi Hong

aut / cre

Henry S. Lynn

ths

Material

README
NEWS
Reference manual
Package source

Vignettes

Introduction to RfEmpImp

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

RfEmpImp archive

Depends

R ≥ 3.5.0
mice ≥ 3.9.0
ranger ≥ 0.12.1

Suggests

testthat ≥ 2.1.0
knitr
rmarkdown