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SCGLR (version 2.0.3)

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

208

Version

2.0.3

License

CeCILL-2 | GPL-2

Maintainer

Guillaume Cornu

Last Published

March 16th, 2016

Functions in SCGLR (2.0.3)

scglrCrossVal

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

customize

Plot customization

infoCriterion

Function that calculates cross-validation selection criteria

barplot.SCGLR

Barplot of percent of overall X variance captured by component

genus

Sample dataset of abundance of genera in tropical moist forest

scglr

Function that fits the scglr model

Methods

Regularization criterion types

pairs.SCGLR

Pairwise scglr plot on components

summary.SCGLR

Summarizing SCGLR fits

plot.SCGLR

SCGLR generic plot

multivariatePredictGlm

Function that predicts the responses from the covariates for a new sample

multivariateGlm.fit

Multivariate generalized linear regression

scglr-package

Supervised Component Generalized Linear Regression

Auxiliary function for controlling SCGLR fitting