Package: missForestPredict
Type: Package
Title: Missing Value Imputation using Random Forest for Prediction
        Settings
Version: 1.0.1
Date: 2025-05-23
Authors@R: c(
    person("Elena", "Albu", , "elenaa.albu@gmail.com", c("aut", "cre"),
           comment = c(ORCID = "0000-0003-2602-0918", funding = "KU Leuven"))
           )
Depends: R (>= 4.0)
Imports: ranger, methods, stats
Suggests: knitr, rmarkdown, ggplot2, dplyr, tidyr
Description: Missing data imputation based on the 'missForest'
        algorithm (Stekhoven, Daniel J (2012)
        <doi:10.1093/bioinformatics/btr597>) with adaptations for
        prediction settings. The function missForest() is used to
        impute a (training) dataset with missing values and to learn
        imputation models that can be later used for imputing new
        observations. The function missForestPredict() is used to
        impute one or multiple new observations (test set) using the
        models learned on the training data. For more details see Albu,
        E., Gao, S., Wynants, L., & Van Calster, B. (2024).
        missForestPredict--Missing data imputation for prediction
        settings <doi:10.48550/arXiv.2407.03379>.
Encoding: UTF-8
License: GPL (>= 2)
URL: https://github.com/sibipx/missForestPredict
BugReports: https://github.com/sibipx/missForestPredict/issues
RoxygenNote: 7.3.2
VignetteBuilder: knitr
Repository: https://sibipx.r-universe.dev
Date/Publication: 2025-05-26 15:10:59 UTC
RemoteUrl: https://github.com/sibipx/missforestpredict
RemoteRef: HEAD
RemoteSha: 22c6aa59a188051cf349a05c341b489a524575c6
NeedsCompilation: no
Packaged: 2026-09-26 07:45:21 UTC; root
Author: Elena Albu [aut, cre] (ORCID: <https://orcid.org/0000-0003-2602-0918>,
    funding: KU Leuven)
Maintainer: Elena Albu <elenaa.albu@gmail.com>