Package: POCRE 0.6.0

Dabao Zhang

POCRE: Penalized Orthogonal-Components Regression

Penalized orthogonal-components regression (POCRE) is a supervised dimension reduction method for high-dimensional data. It sequentially constructs orthogonal components (with selected features) which are maximally correlated to the response residuals. POCRE can also construct common components for multiple responses and thus build up latent-variable models.

Authors:Dabao Zhang, Zhongli Jiang, Zeyu Zhang, Yu-ting Chen

POCRE_0.6.0.tar.gz
POCRE_0.6.0.zip(r-4.7-any)POCRE_0.6.0.zip(r-4.6-any)POCRE_0.6.0.zip(r-4.5-any)
POCRE_0.6.0.tgz(r-4.6-any)POCRE_0.6.0.tgz(r-4.5-any)
POCRE_0.6.0.tar.gz(r-4.7-any)POCRE_0.6.0.tar.gz(r-4.6-any)
POCRE_0.6.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
POCRE/json (API)

# Install 'POCRE' in R:
install.packages('POCRE', repos = c('https://cranhaven.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/cranhaven/cranhaven.r-universe.dev/issues

Datasets:
  • sim5ydata - A Set of Simulated Data with Multiple Response Variables
  • simbin - A Set of Simulated Binomial Data.
  • simdata - A Set of Simulated Data with Single Gaussian Response Variable
  • simpoi - A Set of Simulated Poisson Data.

On CRAN:

Conda:

archivedpackagesr-universe

2.30 score 5 stars 255 downloads 4 mentions 7 exports 21 dependencies

Last updated from:85b64b199a (on package/POCRE). Checks:9 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-develOK130
source / vignettesOK149
linux-releaseOK145
macos-releaseOK94
macos-oldrelOK73
windows-develOK89
windows-releaseOK77
windows-oldrelOK86
wasm-releaseOK102

Exports:cvpocregpspocrepocrepathpocrescreenselectmodelsipocre

Dependencies:clicpp11EbayesThreshfarverggplot2gluegtableisobandlabelinglifecycleMASSpracmaR6RColorBrewerrlangS7scalesvctrsviridisLitewavethreshwithr