R: Nonparametric Missing Value Imputation using Random Forest

missForest-package {missForest} | R Documentation

## Nonparametric Missing Value Imputation using Random Forest

### Description

'missForest' is used to impute missing values particularly in the case of mixed-type data. It can be used to impute continuous and/or categorical data including complex interactions and nonlinear relations. It yields an out-of-bag (OOB) imputation error estimate. Moreover, it can be run parallel to save computation time.

### Details

Package: | missForest
Type: | Package
Version: | 1.4
Date: | 2013-12-31
License: | GPL (>= 2)
LazyLoad: | yes

The main function of the package is `missForest` implementing the nonparametric missing value imputation. See `missForest` for more details.

### Author(s)

Daniel J. Stekhoven, stekhoven@stat.math.ethz.ch

### References

Stekhoven, D.J. and Buehlmann, P. (2012), 'MissForest - nonparametric missing value imputation for mixed-type data', Bioinformatics, 28(1) 2012, 112-118, doi: 10.1093/bioinformatics/btr597

[Package missForest version 1.4 Index]