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-any)SCGLR_3.1.9000.zip(r-4.6-any)SCGLR_3.1.9000.zip(r-4.5-any)
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

3.80 score 2 stars 63 scripts 319 downloads 11 exports 28 dependencies

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

TargetResultTimeFilesSyslog
linux-develOK153
source / vignettesOK185
linux-releaseOK131
macos-releaseOK187
macos-oldrelOK135
windows-develOK112
windows-releaseOK87
windows-oldrelOK115
wasm-releaseOK87

Exports:critConvergenceinfoCriterionkCompRandmethodSRmultivariateFormulamultivariateGlm.fitmultivariatePredictGlmscglrscglrCrossValscglrThemescglrThemeBackward

Dependencies:ade4clicpp11farverFormulaggplot2gluegtableisobandlabelinglatticelifecycleMASSMatrixpixmapplspROCR6RColorBrewerRcppRcppArmadillorlangS7scalesspvctrsviridisLitewithr