Package: booami
Language: en-US
Type: Package
Title: Component-Wise Gradient Boosting after Multiple Imputation
Version: 0.1.1
Authors@R: 
    person("Robert", "Kuchen", email = "rokuchen@uni-mainz.de", 
           role = c("aut", "cre"))
Description: Component-wise gradient boosting for analysis of multiply
    imputed datasets. Implements the algorithm Boosting after Multiple
    Imputation (MIBoost), which enforces uniform variable selection across
    imputations and provides utilities for pooling. Includes a cross-validation
    workflow that first splits the data into training and validation sets and
    then performs imputation on the training data, applying the learned
    imputation models to the validation data to avoid information leakage.
    Supports Gaussian and logistic loss. Methods relate to gradient boosting
    and multiple imputation as in Buehlmann and Hothorn (2007) <doi:10.1214/07-STS242>,
    Friedman (2001) <doi:10.1214/aos/1013203451>, and van Buuren (2018, ISBN:9781138588318)
    and Groothuis-Oudshoorn (2011) <doi:10.18637/jss.v045.i03>; see also Kuchen (2025)
    <doi:10.48550/arXiv.2507.21807>.
License: MIT + file LICENSE
URL: https://arxiv.org/abs/2507.21807,
        https://github.com/RobertKuchen/booami
BugReports: https://github.com/RobertKuchen/booami/issues
Encoding: UTF-8
Depends: R (>= 4.0)
Imports: MASS, stats, utils, withr
Suggests: mice, miceadds, Matrix, knitr, rmarkdown, testthat (>=
        3.0.0), spelling
Config/testthat/edition: 3
RoxygenNote: 7.3.2
LazyData: true
NeedsCompilation: no
Packaged: 2025-09-30 14:04:09 UTC; rokuchen
Author: Robert Kuchen [aut, cre]
Maintainer: Robert Kuchen <rokuchen@uni-mainz.de>
Repository: CRAN
Date/Publication: 2025-09-30 14:40:02 UTC
Built: R 4.4.3; ; 2025-10-21 12:03:04 UTC; windows
