bigRR: 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.

Package details

AuthorXia Shen, Moudud Alam and Lars Ronnegard
MaintainerXia Shen <[email protected]>
LicenseGPL (>= 2)
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the bigRR package in your browser

Any scripts or data that you put into this service are public.

bigRR documentation built on May 29, 2017, 9:29 p.m.