Package: glmtrans
Type: Package
Title: Transfer Learning under Regularized Generalized Linear Models
Version: 2.1.0
Authors@R: c(person("Ye", "Tian", role = c("aut", "cre"), email = "ye.t@columbia.edu"), person("Yang", "Feng", role = "aut", email = "yang.feng@nyu.edu"))
Description: We provide an efficient implementation for two-step
        multi-source transfer learning algorithms in high-dimensional
        generalized linear models (GLMs). The elastic-net penalized GLM
        with three popular families, including linear, logistic and
        Poisson regression models, can be fitted. To avoid negative
        transfer, a transferable source detection algorithm is
        proposed. We also provides visualization for the transferable
        source detection results. The details of methods can be found
        in "Tian, Y., & Feng, Y. (2023). Transfer learning under
        high-dimensional generalized linear models. Journal of the
        American Statistical Association, 118(544), 2684-2697.".
Imports: glmnet, ggplot2, foreach, doParallel, caret, assertthat,
        formatR, stats
License: GPL-2
Depends: R (>= 3.5.0)
Encoding: UTF-8
RoxygenNote: 7.3.2
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-07-10 08:00:50 UTC; root
Author: Ye Tian [aut, cre], Yang Feng [aut]
Maintainer: Ye Tian <ye.t@columbia.edu>
Config/pak/sysreqs: libicu-dev
Repository: https://ytstat.r-universe.dev
Date/Publication: 2025-03-01 01:40:08 UTC
RemoteUrl: https://github.com/cran/glmtrans
RemoteRef: HEAD
RemoteSha: c27f1f5f3aa531d8ca4071ad359d47a7e3160635