Package: SiER 0.1.0
SiER: Signal Extraction Approach for Sparse Multivariate Response Regression
Methods for regression with high-dimensional predictors and univariate or maltivariate response variables. It considers the decomposition of the coefficient matrix that leads to the best approximation to the signal part in the response given any rank, and estimates the decomposition by solving a penalized generalized eigenvalue problem followed by a least squares procedure. Ruiyan Luo and Xin Qi (2017) <doi:10.1016/j.jmva.2016.09.005>.
Authors:
SiER_0.1.0.tar.gz
SiER_0.1.0.zip(r-4.5)SiER_0.1.0.zip(r-4.4)SiER_0.1.0.zip(r-4.3)
SiER_0.1.0.tgz(r-4.4-any)SiER_0.1.0.tgz(r-4.3-any)
SiER_0.1.0.tar.gz(r-4.5-noble)SiER_0.1.0.tar.gz(r-4.4-noble)
SiER_0.1.0.tgz(r-4.4-emscripten)SiER_0.1.0.tgz(r-4.3-emscripten)
SiER.pdf |SiER.html✨
SiER/json (API)
| # Install 'SiER' in R: |
| install.packages('SiER', repos = c('https://rruiyan.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 7 years agofrom:cd22b18850. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 31 2024 |
| R-4.5-win | OK | Oct 31 2024 |
| R-4.5-linux | OK | Oct 31 2024 |
| R-4.4-win | OK | Oct 31 2024 |
| R-4.4-mac | OK | Oct 31 2024 |
| R-4.3-win | OK | Oct 31 2024 |
| R-4.3-mac | OK | Oct 31 2024 |
Exports:cv.SiERgetcoef.SiERpred.SiER
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Cross-validation for high-dimensional multivariate regression | cv.SiER |
| Get the estimated intercept and coefficient. | getcoef.SiER |
| Prediction for high-dimensional multivariate regression | pred.SiER |
