Package: glmtrans
Type: Package
Title: Transfer Learning with Regularized Generalized Linear Models
Version: 1.0.0
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 models, can be fitted. To avoid negative transfer, a transferable source detection algorithm is available. We also provides visualization for the transferable source detection results. A relevant paper
    by Ye Tian and Yang Feng (2021) will be available soon on arXiv.
Imports: glmnet, ggplot2, foreach, doParallel, caret, assertthat,
        formatR, stats
License: GPL-2
Depends: R (>= 3.5.0)
Encoding: UTF-8
LazyData: TRUE
RoxygenNote: 7.1.0
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-04-27 02:48:27 UTC; yetian
Author: Ye Tian [aut, cre],
  Yang Feng [aut]
Maintainer: Ye Tian <ye.t@columbia.edu>
Repository: CRAN
Date/Publication: 2021-04-28 07:50:02 UTC
