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bigRR (version 1.3-10)

Generalized Ridge Regression (with special advantage for p >> n cases)

Description

The package fits large-scale (generalized) ridge regression for various distributions of response. The shrinkage parameters (lambdas) can be pre-specified or estimated using an internal update routine (fitting a heteroscedastic effects model, or HEM). It gives possibility to shrink any subset of parameters in the model. It has special computational advantage for the cases when the number of shrinkage parameters exceeds the number of observations. For example, the package is very useful for fitting large-scale omics data, such as high-throughput genotype data (genomics), gene expression data (transcriptomics), metabolomics data, etc.

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Version

Install

install.packages('bigRR')

Monthly Downloads

45

Version

1.3-10

License

GPL (>= 2)

Maintainer

Last Published

August 23rd, 2014

Functions in bigRR (1.3-10)

plot.bigRR

Plot method for bigRR objects
bigRR-package

Generalized Ridge Regression (with special advantage for p >> n cases)
bigRR_update

Updating a bigRR fit to be a heteroscedastic effects model (HEM) fit
hugeRR_update

Updating a hugeRR fit to be a heteroscedastic effects model (HEM) fit
y

See ‘Arabidopsis’
hugeRR

Fitting big ridge regression
Z.FTIR

See ‘Chemometrics’
Chemometrics

An Ethanol data set with FTIR spectrum data
Z

See ‘Arabidopsis’
print.bigRR

Print method for bigRR objects
ethanol

See ‘Chemometrics’
Arabidopsis

Arabidopsis thaliana data set from Atwell et al. 2010 Nature
bigRR

Fitting big ridge regression