glmtrans

Transfer Learning under Regularized Generalized Linear Models

CRAN Package

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.".

  • Version2.1.0
  • R versionR (≥ 3.5.0)
  • LicenseGPL-2
  • Needs compilation?No
  • Last release03/01/2025

Documentation


Team


Insights

Last 30 days

This package has been downloaded 249 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 9 times.

Sun
Mon
Tue
Wed
Thu
Fri
Sat
0 downloadsMar 2, 2025
15 downloadsMar 3, 2025
27 downloadsMar 4, 2025
15 downloadsMar 5, 2025
5 downloadsMar 6, 2025
7 downloadsMar 7, 2025
17 downloadsMar 8, 2025
1 downloadsMar 9, 2025
0 downloadsMar 10, 2025
10 downloadsMar 11, 2025
4 downloadsMar 12, 2025
11 downloadsMar 13, 2025
5 downloadsMar 14, 2025
10 downloadsMar 15, 2025
1 downloadsMar 16, 2025
3 downloadsMar 17, 2025
6 downloadsMar 18, 2025
3 downloadsMar 19, 2025
19 downloadsMar 20, 2025
9 downloadsMar 21, 2025
10 downloadsMar 22, 2025
11 downloadsMar 23, 2025
7 downloadsMar 24, 2025
4 downloadsMar 25, 2025
6 downloadsMar 26, 2025
14 downloadsMar 27, 2025
8 downloadsMar 28, 2025
6 downloadsMar 29, 2025
4 downloadsMar 30, 2025
2 downloadsMar 31, 2025
9 downloadsApr 1, 2025
0 downloadsApr 2, 2025
0 downloadsApr 3, 2025
0 downloadsApr 4, 2025
0 downloadsApr 5, 2025
0
27

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 2,541 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Jul 21, 2024 with 70 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Data provided by CRAN


Binaries


Dependencies

  • Imports7 packages
  • Suggests2 packages
  • Reverse Suggests1 package