Package: joinet 1.0.0
joinet: Penalised Multivariate Regression ('Multi-Target Learning')
Implements penalised multivariate regression (i.e., for multiple outcomes and many features) by stacked generalisation (<doi:10.1093/bioinformatics/btab576>). For positively correlated outcomes, a single multivariate regression is typically more predictive than multiple univariate regressions. Includes functions for model fitting, extracting coefficients, outcome prediction, and performance measurement. For optional comparisons, install 'remMap' from GitHub (<https://github.com/cran/remMap>).
Authors:
joinet_1.0.0.tar.gz
joinet_1.0.0.zip(r-4.5)joinet_1.0.0.zip(r-4.4)joinet_1.0.0.zip(r-4.3)
joinet_1.0.0.tgz(r-4.4-any)joinet_1.0.0.tgz(r-4.3-any)
joinet_1.0.0.tar.gz(r-4.5-noble)joinet_1.0.0.tar.gz(r-4.4-noble)
joinet_1.0.0.tgz(r-4.4-emscripten)joinet_1.0.0.tgz(r-4.3-emscripten)
joinet.pdf |joinet.html✨
joinet/json (API)
NEWS
# Install 'joinet' in R: |
install.packages('joinet', repos = c('https://rauschenberger.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/rauschenberger/joinet/issues
Last updated 2 months agofrom:d5f0b58128. Checks:OK: 3 NOTE: 4. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 27 2024 |
R-4.5-win | OK | Oct 27 2024 |
R-4.5-linux | OK | Oct 27 2024 |
R-4.4-win | NOTE | Oct 27 2024 |
R-4.4-mac | NOTE | Oct 27 2024 |
R-4.3-win | NOTE | Oct 27 2024 |
R-4.3-mac | NOTE | Oct 27 2024 |
Dependencies:codetoolscornetforeachglmnetiteratorslatticeMatrixpalassoRcppRcppEigenshapesurvival
Multivariate Elastic Net Regression
Rendered fromscript.Rmd
usingknitr::rmarkdown
on Oct 27 2024.Last update: 2021-07-14
Started: 2020-12-01
Multivariate Elastic Net Regression
Rendered fromarticle.Rmd
usingknitr::rmarkdown
on Oct 27 2024.Last update: 2024-09-27
Started: 2019-03-18
Multivariate Elastic Net Regression
Rendered fromvignette.Rmd
usingknitr::rmarkdown
on Oct 27 2024.Last update: 2024-09-27
Started: 2018-06-14
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Multivariate Elastic Net Regression | joinet-package |
Extract Coefficients | coef.joinet |
Model comparison | cv.joinet |
Multivariate Elastic Net Regression | joinet |
Make Predictions | predict.joinet |
Extract Weights | weights.joinet |