Package: SCGLR 3.0.9000

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]

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SCGLR.pdf |SCGLR.html
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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 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-Forge:

partial-least-squares-regression

4.30 score 2 stars 67 scripts 263 downloads 11 exports 37 dependencies

Last updated 10 days agofrom:98a0dd7ed3. Checks:8 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 24 2025
R-4.5-winOKFeb 24 2025
R-4.5-macOKFeb 24 2025
R-4.5-linuxOKFeb 24 2025
R-4.4-winOKFeb 24 2025
R-4.4-macOKFeb 24 2025
R-4.3-winOKFeb 24 2025
R-4.3-macOKFeb 24 2025

Exports:critConvergenceinfoCriterionkCompRandmethodSRmultivariateFormulamultivariateGlm.fitmultivariatePredictGlmscglrscglrCrossValscglrThemescglrThemeBackward

Dependencies:ade4clicolorspacefansifarverFormulaggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpixmappkgconfigplsplyrpROCR6RColorBrewerRcppRcppArmadillorlangscalessptibbleutf8vctrsviridisLitewithr