missForest: Nonparametric Missing Value Imputation using Random Forest
Version 1.4

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.

Package details

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)
Version1.4
URL http://www.r-project.org https://github.com/stekhoven/missForest
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("missForest")

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missForest documentation built on May 29, 2017, 10:47 a.m.