glmtrans: Transfer Learning under Regularized Generalized Linear Models

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.".

Package details

AuthorYe Tian [aut, cre], Yang Feng [aut]
MaintainerYe Tian <ye.t@columbia.edu>
LicenseGPL-2
Version2.1.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("glmtrans")

Try the glmtrans package in your browser

Any scripts or data that you put into this service are public.

glmtrans documentation built on April 4, 2025, 12:32 a.m.