Package: missForest
Type: Package
Title: Nonparametric Missing Value Imputation using Random Forest
Version: 1.5
Date: 2022-04-14
Author: Daniel J. Stekhoven <stekhoven@stat.math.ethz.ch>
Maintainer: Daniel J. Stekhoven <stekhoven@stat.math.ethz.ch>
Imports: randomForest,foreach,itertools,iterators,doRNG
Suggests: doParallel
Description: 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.
License: GPL (>= 2)
URL: https://www.r-project.org, https://github.com/stekhoven/missForest
NeedsCompilation: no
Packaged: 2022-04-14 14:13:03 UTC; danistek
Repository: CRAN
Date/Publication: 2022-04-14 14:52:29 UTC
Built: R 4.3.3; ; 2025-01-24 18:03:22 UTC; unix
