The function ‘missForest’ in this package is used to impute missing values particularly in the case of mixed-type data. It uses a random forest trained on the observed values of a data matrix to predict the missing values. It can be used to impute continuous and/or categorical data including complex interactions and non-linear relations. It yields an out-of-bag (OOB) imputation error estimate without the need of a test set or elaborate cross-validation. It can be run in parallel to save computation time.

Home http://www.r-project.org, https://github.com/stekhoven/missForest
Versions 1.4
License GPL (>= 2)
Recipe https://github.com/bioconda/bioconda-recipes/tree/master/recipes/r-missforest


With an activated Bioconda channel (see 2. Set up channels), install with:

conda install r-missforest

and update with:

conda update r-missforest


A Docker container is available at https://quay.io/repository/biocontainers/r-missforest.