Package: irboost
Type: Package
Title: Iteratively Reweighted Boosting for Robust Analysis
Version: 0.2-1.1
Date: 2026-03-13
Authors@R: c(person("Zhu", "Wang", role = c("aut", "cre"),
                    email = "zwang145@uthsc.edu", 
                    comment = c(ORCID = "0000-0002-0773-0052")))
Author: Zhu Wang [aut, cre] (ORCID:
        <https://orcid.org/0000-0002-0773-0052>)
Maintainer: Zhu Wang <zwang145@uthsc.edu>
Description: Fit a predictive model using iteratively reweighted
        boosting (IRBoost) to minimize robust loss functions within the
        CC-family (concave-convex). This constitutes an application of
        iteratively reweighted convex optimization (IRCO), where convex
        optimization is performed using the functional descent boosting
        algorithm. IRBoost assigns weights to facilitate outlier
        identification. Applications include robust generalized linear
        models and robust accelerated failure time models. Wang (2025)
        <doi:10.6339/24-JDS1138>.
Depends: R (>= 3.5.0)
Imports: mpath (>= 0.4-2.21), xgboost
Suggests: R.rsp, DiagrammeR, survival, Hmisc
VignetteBuilder: R.rsp
License: GPL (>= 3)
Encoding: UTF-8
LazyLoad: yes
Packaged: 2026-06-14 09:12:07 UTC; root
RoxygenNote: 7.3.3
NeedsCompilation: no
Config/pak/sysreqs: make
Repository: https://zhuwang46.r-universe.dev
Date/Publication: 2026-03-17 12:20:10 UTC
RemoteUrl: https://github.com/cran/irboost
RemoteRef: HEAD
RemoteSha: aa62d635fcb8f1b0f3d51c0221b3318f27e96674