# bigRR v1.3-10

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

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.

## Functions in bigRR

 Name Description 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 No Results!