Package: harf
Title: Adversarial Random Forests for Omics Synthesis
Version: 0.1.0
Authors@R: 
    c(person(given = c("Cesaire", "J.", "K."),
           family = "Fouodo",
           role = c("aut", "cre"),
           email = "fouodo@leibniz-bips.de"),
      person(
        given = c("Jan"),
        family = "Kapar",
        role = "aut"
    ),
    person(
        given = c("Marvin", "N."),
        family = "Wright",
        role = "aut"
    )
      )
Description: We extend Adversarial Random Forests to a high-dimensional
    framework. The method partitions the feature space into regions where the
    assumption of feature independence within tree leaves is more likely to
    hold. Region-specific adversarial random forest models are trained to
    capture local dependence structures, while an additional adversarial
    random forest is fitted to a meta-space representation to model
    dependencies between regions. New observations are generated by first
    sampling from the meta-space model and then conditionally sampling from
    each region-specific model. The proposed methodology is described in
    Fouodo et al. (2026) <doi:10.64898/2026.09.09.750490>.
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.3.3
Imports: arf, data.table, stats, ClusterR, matrixStats, pracma, pls,
        fastPLS, RGCCA, ranger, rsvd, foreach
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, checkmate, Rtsne,
        SingleCellExperiment, corrplot, scater, cowplot, ggplot2,
        doParallel, pROC, caret
Config/testthat/edition: 3
Depends: R (>= 3.6.0)
Collate: 'single_cell.R' 'kich.R' 'utils.R' 'h_arf.R' 'h_forge.R'
VignetteBuilder: knitr, rmarkdown
BugReports: https://github.com/bips-hb/harf/issues
LazyData: true
URL: https://bips-hb.github.io/harf/
NeedsCompilation: no
Packaged: 2026-09-18 00:52:40 UTC; CKUETEF
Author: Cesaire J. K. Fouodo [aut, cre],
  Jan Kapar [aut],
  Marvin N. Wright [aut]
Maintainer: Cesaire J. K. Fouodo <fouodo@leibniz-bips.de>
Repository: CRAN
Date/Publication: 2026-09-28 09:00:18 UTC
