Package: missRanger
Title: Fast Imputation of Missing Values
Version: 2.6.1
Authors@R: 
    person("Michael", "Mayer", , "mayermichael79@gmail.com", role = c("aut", "cre"))
Description: 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)
    <doi: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.
License: GPL (>= 2)
Depends: R (>= 3.5.0)
Encoding: UTF-8
RoxygenNote: 7.3.2
Imports: FNN, ranger (>= 0.16.0), stats, utils
URL: https://github.com/mayer79/missRanger,
        https://mayer79.github.io/missRanger/
BugReports: https://github.com/mayer79/missRanger/issues
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2024-12-07 08:49:20 UTC; mayer
Author: Michael Mayer [aut, cre]
Maintainer: Michael Mayer <mayermichael79@gmail.com>
Repository: CRAN
Date/Publication: 2024-12-07 09:20:02 UTC
Built: R 4.6.0; ; 2026-04-26 03:51:32 UTC; unix
