Package: SCGLR 3.1.9000

Guillaume Cornu

SCGLR: Supervised Component Generalized Linear Regression

An extension of the Fisher Scoring Algorithm to combine PLS regression with GLM estimation in the multivariate context. Covariates can also be grouped in themes.

Authors:Guillaume Cornu [aut, cre], Frederic Mortier [aut], Catherine Trottier [aut], Xavier Bry [aut], Jocelyn Chauvet [aut], Sylvie Gourlet-Fleury [dtc], Claude Garcia [dtc], GAMBAS [fnd]

SCGLR_3.1.9000.tar.gz
SCGLR_3.1.9000.zip(r-4.7)SCGLR_3.1.9000.zip(r-4.6)SCGLR_3.1.9000.zip(r-4.5)
SCGLR_3.1.9000.tgz(r-4.6-any)SCGLR_3.1.9000.tgz(r-4.5-any)
SCGLR_3.1.9000.tar.gz(r-4.7-any)SCGLR_3.1.9000.tar.gz(r-4.6-any)
SCGLR_3.1.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
SCGLR/json (API)

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

Bug tracker:https://github.com/scnext/scglr/issues

Pkgdown/docs site:https://scnext.github.io

Datasets:
  • dataGen - Sample dataset of abundance of genera in tropical moist forest
  • genus - Sample dataset of abundance of genera in tropical moist forest
  • genus2 - Sample dataset of abundance of genera in tropical moist forest

On CRAN:

Conda:

partial-least-squares-regression

3.81 score 2 stars 65 scripts 192 downloads 11 exports 28 dependencies

Last updated from:01d669f062. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK139
source / vignettesOK244
linux-release-x86_64OK128
macos-release-arm64OK150
macos-oldrel-arm64OK176
windows-develOK119
windows-releaseOK107
windows-oldrelOK107
wasm-releaseOK104

Exports:critConvergenceinfoCriterionkCompRandmethodSRmultivariateFormulamultivariateGlm.fitmultivariatePredictGlmscglrscglrCrossValscglrThemescglrThemeBackward

Dependencies:ade4clicpp11farverFormulaggplot2gluegtableisobandlabelinglatticelifecycleMASSMatrixpixmapplspROCR6RColorBrewerRcppRcppArmadillorlangS7scalesspvctrsviridisLitewithr