Package: OHPL 1.4.1
![](https://github.com/cran/OHPL/raw/HEAD/man/figures/logo.png)
OHPL: Ordered Homogeneity Pursuit Lasso for Group Variable Selection
Ordered homogeneity pursuit lasso (OHPL) algorithm for group variable selection proposed in Lin et al. (2017) <doi:10.1016/j.chemolab.2017.07.004>. The OHPL method exploits the homogeneity structure in high-dimensional data and enjoys the grouping effect to select groups of important variables automatically. This feature makes it particularly useful for high-dimensional datasets with strongly correlated variables, such as spectroscopic data.
Authors:
OHPL_1.4.1.tar.gz
OHPL_1.4.1.tar.gz(r-4.5-noble)OHPL_1.4.1.tar.gz(r-4.4-noble)
OHPL_1.4.1.tgz(r-4.4-emscripten)OHPL_1.4.1.tgz(r-4.3-emscripten)
OHPL.pdf |OHPL.html✨
OHPL/json (API)
NEWS
# Install 'OHPL' in R: |
install.packages('OHPL', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/nanxstats/ohpl/issues
Last updated 2 months agofrom:ae86c25f46. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Aug 20 2024 |
R-4.5-linux | OK | Aug 20 2024 |
Exports:cv.OHPLdlcFOPOHPLOHPL.RMSEPOHPL.simproto
Dependencies:codetoolsforeachglmnetiteratorslatticeMatrixmvtnormplsRcppRcppEigenshapesurvival