Package: logicDT
Type: Package
Title: Identifying Interactions Between Binary Predictors
Version: 1.0.5
Authors@R: person("Michael", "Lau", email = "michael.lau@hhu.de",
  role = c("aut", "cre"), comment = c(ORCID = "0000-0002-5327-8351"))
Description: A statistical learning method that tries to find the best
        set of predictors and interactions between predictors for
        modeling binary or quantitative response data in a decision
        tree. Several search algorithms and ensembling techniques are
        implemented allowing for finetuning the method to the specific
        problem. Interactions with quantitative covariables can be
        properly taken into account by fitting local regression models.
        Moreover, a variable importance measure for assessing marginal
        and interaction effects is provided. Implements the procedures
        proposed by Lau et al. (2024,
        <doi:10.1007/s10994-023-06488-6>).
License: MIT + file LICENSE
Encoding: UTF-8
Imports: glmnet, graphics, stats, utils
RoxygenNote: 7.1.2
NeedsCompilation: yes
Packaged: 2026-10-03 08:33:52 UTC; root
Author: Michael Lau [aut, cre]
        (<https://orcid.org/0000-0002-5327-8351>)
Maintainer: Michael Lau <michael.lau@hhu.de>
Repository: https://michlau.r-universe.dev
Date/Publication: 2024-09-24 03:02:07 UTC
RemoteUrl: https://github.com/cran/logicDT
RemoteRef: HEAD
RemoteSha: e9a2eeff7913ec0816bdf11bc4d8f9de9cdfd035