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IBLM: Interpretable Boosted Linear Models

Implements Interpretable Boosted Linear Models (IBLMs). These combine a conventional generalized linear model (GLM) with a machine learning component, such as XGBoost. The package also provides tools within for explaining and analyzing these models. For more details see Gawlowski and Wang (2025) <https://ifoa-adswp.github.io/IBLM/reference/figures/iblm_paper.pdf>.

Version: 1.0.1
Depends: R (≥ 4.1.0)
Imports: cli, dplyr, fastDummies, ggExtra, ggplot2, purrr, scales, statmod, stats, utils, withr, xgboost
Suggests: testthat (≥ 3.0.0)
Published: 2025-11-19
DOI: 10.32614/CRAN.package.IBLM (may not be active yet)
Author: Karol Gawlowski [aut, cre, cph], Paul Beard [aut]
Maintainer: Karol Gawlowski <Karol.Gawlowski at citystgeorges.ac.uk>
BugReports: https://github.com/IFoA-ADSWP/IBLM/issues
License: MIT + file LICENSE
URL: https://ifoa-adswp.github.io/IBLM/, https://github.com/IFoA-ADSWP/IBLM
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: IBLM results

Documentation:

Reference manual: IBLM.html , IBLM.pdf

Downloads:

Package source: IBLM_1.0.1.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): IBLM_1.0.1.tgz, r-oldrel (x86_64): IBLM_1.0.1.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=IBLM to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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