Package: transreg 1.0.3
transreg: Penalised Regression with Multiple Sets of Prior Effects ('Transfer Learning')
Improves the predictive performance of ridge and lasso regression exploiting one or more sources of prior information on the importance and direction of effects (Rauschenberger and others 2023, <doi:10.1093/bioinformatics/btad680>). For running the vignette (optional), install 'fwelnet' from 'GitHub' <https://github.com/kjytay/fwelnet>.
Authors:
transreg_1.0.3.tar.gz
transreg_1.0.3.zip(r-4.5)transreg_1.0.3.zip(r-4.4)transreg_1.0.3.zip(r-4.3)
transreg_1.0.3.tgz(r-4.4-any)transreg_1.0.3.tgz(r-4.3-any)
transreg_1.0.3.tar.gz(r-4.5-noble)transreg_1.0.3.tar.gz(r-4.4-noble)
transreg_1.0.3.tgz(r-4.4-emscripten)transreg_1.0.3.tgz(r-4.3-emscripten)
transreg.pdf |transreg.html✨
transreg/json (API)
NEWS
# Install 'transreg' in R: |
install.packages('transreg', repos = c('https://rauschenberger.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/rauschenberger/transreg/issues
Last updated 2 months agofrom:4c35c57861. Checks:OK: 3 NOTE: 4. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 28 2024 |
R-4.5-win | OK | Oct 28 2024 |
R-4.5-linux | OK | Oct 28 2024 |
R-4.4-win | NOTE | Oct 28 2024 |
R-4.4-mac | NOTE | Oct 28 2024 |
R-4.3-win | NOTE | Oct 28 2024 |
R-4.3-mac | NOTE | Oct 28 2024 |
Exports:transreg
Dependencies:codetoolscornetforeachglmnetiteratorsjoinetlatticeMatrixpalassoRcppRcppEigenshapestarnetsurvival
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Penalised regression with multiple sets of prior effects | transreg-package |
Calculate residuals | .residuals |
Sign discovery | .signdisc |
Internal functions | .exp.multiple .iso.fast.single .iso.multiple .iso.slow.single calibrate |
Extract Coefficients | coef.transreg |
Cross-validation (reproducibility) | compare |
Internal functions | .coef.sim .coef.sta .predict.sim .predict.sta .weights.sim .weights.sta .which.stack extract |
Fitted values | fitted.transreg |
Plot transreg-object | plot.transreg |
Make Predictions | predict.transreg |
Print transreg-object | print.transreg |
Simulation (reproducibility) | simulate |
Penalised regression with multiple sets of prior effects | transreg |
Extract Weights | weights.transreg |