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cff-version: 1.2.0
message: 'To cite package "missRanger" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'missRanger: Fast Imputation of Missing Values'
version: 2.6.1
doi: 10.32614/CRAN.package.missRanger
abstract: Alternative implementation of the beautiful 'MissForest' algorithm used
  to impute mixed-type data sets by chaining random forests, introduced by Stekhoven,
  D.J. and Buehlmann, P. (2012) <https://doi.org/10.1093/bioinformatics/btr597>. Under
  the hood, it uses the lightning fast random forest package 'ranger'. Between the
  iterative model fitting, we offer the option of using predictive mean matching.
  This firstly avoids imputation with values not already present in the original data
  (like a value 0.3334 in 0-1 coded variable). Secondly, predictive mean matching
  tries to raise the variance in the resulting conditional distributions to a realistic
  level. This would allow, e.g., to do multiple imputation when repeating the call
  to missRanger(). Out-of-sample application is supported as well.
authors:
- family-names: Mayer
  given-names: Michael
  email: mayermichael79@gmail.com
repository: https://CRAN.R-project.org/package=missRanger
repository-code: https://github.com/mayer79/missRanger
url: https://mayer79.github.io/missRanger/
date-released: '2024-12-07'
contact:
- family-names: Mayer
  given-names: Michael
  email: mayermichael79@gmail.com