Package: glmtrans 2.1.0
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.".
Authors:
glmtrans_2.1.0.tar.gz
glmtrans_2.1.0.zip(r-4.7-any)glmtrans_2.1.0.zip(r-4.6-any)glmtrans_2.1.0.zip(r-4.5-any)
glmtrans_2.1.0.tgz(r-4.6-any)glmtrans_2.1.0.tgz(r-4.5-any)
glmtrans_2.1.0.tar.gz(r-4.7-any)glmtrans_2.1.0.tar.gz(r-4.6-any)
glmtrans_2.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
glmtrans/json (API)
| # Install 'glmtrans' in R: |
| install.packages('glmtrans', repos = c('https://ytstat.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:c27f1f5f3a. Checks:7 WARNING, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | WARNING | 204 | ||
| source / vignettes | OK | 229 | ||
| linux-release-x86_64 | WARNING | 192 | ||
| macos-release-arm64 | WARNING | 141 | ||
| macos-oldrel-arm64 | WARNING | 155 | ||
| windows-devel | WARNING | 158 | ||
| windows-release | WARNING | 144 | ||
| windows-oldrel | WARNING | 182 | ||
| wasm-release | OK | 133 |
Exports:glmtransglmtrans_infmodelssource_detection
Dependencies:assertthatcaretclasscliclockcodetoolscpp11data.tablediagramdigestdoParalleldplyre1071farverforeachformatRfuturefuture.applygenericsggplot2glmnetglobalsgluegowergtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixModelMetricsnlmennetnumDerivparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcppRcppEigenrecipesreshape2rlangrpartS7scalesshapesparsevctrsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Fit a transfer learning generalized linear model (GLM) with elasticnet regularization. | glmtrans |
| Calculate asymptotic confidence intervals based on desparsified Lasso and two-step transfer learning method. | glmtrans_inf |
| Generate data from Gaussian, logistic and Poisson models. | models |
| Visualize the losses of different sources and the threshold to determine transferability. | plot.glmtrans plot.glmtrans_source_detection |
| Predict for new data from a "glmtrans" object. | predict.glmtrans |
| Print a fitted "glmtrans" object. | print.glmtrans |
| Transferable source detection for GLM transfer learning algorithm. | source_detection |
