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SCGLR (version 2.0.2)

Supervised Component Generalized Linear Regression

Description

The Fisher Scoring Algorithm is extended so as to combine Partial Least Squares regression with Generalized Linear Model estimation in the multivariate context.

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Version

Install

install.packages('SCGLR')

Monthly Downloads

188

Version

2.0.2

License

CeCILL-2 | GPL-2

Maintainer

Guillaume Cornu

Last Published

February 16th, 2015

Functions in SCGLR (2.0.2)

barplot.SCGLR

Barplot of percent of overall X variance captured by component
multivariatePredictGlm

Function that predicts the responses from the covariates for a new sample
multivariateGlm.fit

Multivariate generalized linear regression
Methods

Regularization criterion types
scglr

Function that fits the scglr model
genus

Sample dataset of abundance of genera in tropical moist forest
customize

Plot customization
critConvergence

Auxiliary function for controlling SCGLR fitting
pairs.SCGLR

Pairwise scglr plot on components
multivariateFormula

Formula construction
print.SCGLR

Print SCGLR object
scglrCrossVal

Function that fits and selects the number of component by cross-validation.
scglr-package

Supervised Component Generalized Linear Regression
plot.SCGLR

SCGLR generic plot
infoCriterion

Function that calculates cross-validation selection criteria
summary.SCGLR

Summarizing SCGLR fits