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✨
card.svg |card.png
SCGLR/json (API)
NEWS

# 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

3.79 score 2 stars 61 scripts 229 downloads 11 exports 28 dependencies

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

TargetResultTimeFilesSyslog
linux-devel-x86_64OK143
source / vignettesOK167
linux-release-x86_64OK142
macos-release-arm64OK153
macos-oldrel-arm64OK197
windows-develOK117
windows-releaseOK107
windows-oldrelOK91
wasm-releaseOK108

Exports:critConvergenceinfoCriterionkCompRandmethodSRmultivariateFormulamultivariateGlm.fitmultivariatePredictGlmscglrscglrCrossValscglrThemescglrThemeBackward

Dependencies:ade4clicpp11farverFormulaggplot2gluegtableisobandlabelinglatticelifecycleMASSMatrixpixmapplspROCR6RColorBrewerRcppRcppArmadillorlangS7scalesspvctrsviridisLitewithr