Package: glmtrans
Type: Package
Title: Transfer Learning under Regularized Generalized Linear Models
Version: 2.0.0
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 relevant paper
    is available on arXiv: <arXiv:2105.14328>.
Imports: glmnet, ggplot2, foreach, doParallel, caret, assertthat,
        formatR, stats
License: GPL-2
Depends: R (>= 3.5.0)
Encoding: UTF-8
RoxygenNote: 7.1.2
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-02-07 23:31:09 UTC; yetian
Author: Ye Tian [aut, cre],
  Yang Feng [aut]
Maintainer: Ye Tian <ye.t@columbia.edu>
Repository: CRAN
Date/Publication: 2022-02-08 07:30:02 UTC
