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SCGLR (version 2.0.1)

Supervised Component Generalized Linear Regression (SCGLR)

Description

SCGLR extends the Fisher Scoring Algorithm so as to combine PLS regression with GLM estimation in the multivariate context.

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Version

Install

install.packages('SCGLR')

Monthly Downloads

188

Version

2.0.1

License

CeCILL-2 | GPL-2

Maintainer

Guillaume Cornu

Last Published

October 14th, 2014

Functions in SCGLR (2.0.1)

Methods

Regularization criterion types
customize

Plot customization
infoCriterion

Function that calculates cross-validation selection criteria
barplot.SCGLR

Barplot of percent of overall X variance captured by component
summary.SCGLR

Summarizing SCGLR fits
critConvergence

Auxiliary function for controlling SCGLR fitting
scglr-package

Supervised Component Generalized Linear Regression (SCGLR)
scglrCrossVal

Function that fits and selects the number of component by cross-validation.
pairs.SCGLR

Pairwise scglr plot on components
scglr

Function that fits the scglr model
genus

Sample dataset of abundance of genera in tropical moist forest
multivariatePredictGlm

Function that predicts the responses from the covariates for a new sample
print.SCGLR

Print SCGLR object
multivariateFormula

Formula construction
multivariateGlm.fit

Multivariate generalized linear regression
plot.SCGLR

SCGLR generic plot