missForest: Nonparametric Missing Value Imputation using Random Forest

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.

AuthorDaniel J. Stekhoven <stekhoven@stat.math.ethz.ch>
Date of publication2013-12-31 16:17:04
MaintainerDaniel J. Stekhoven <stekhoven@stat.math.ethz.ch>
LicenseGPL (>= 2)

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