bigRR (1.3-10)

0 users

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

http://cran.r-project.org/web/packages/bigRR

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.

Maintainer: Xia Shen
Author(s): Xia Shen, Moudud Alam and Lars Ronnegard

License: GPL (>= 2)

Uses: DatABEL, hglm
Reverse suggests: GenABEL

Released almost 3 years ago.


2 previous versions

Ratings

Overall:

  (0 votes)

Documentation:

  (0 votes)

Log in to vote.

Reviews

No one has written a review of bigRR yet. Want to be the first? Write one now.


Related packages: BayesTree, ElemStatLearn, GAMBoost, LogicReg, ROCR, RXshrink, arules, caret, e1071, earth, effects, elasticnet, gbm, glmpath, grplasso, ipred, kernlab, klaR, lars, lasso2(20 best matches, based on common tags.)


Search for bigRR on google, google scholar, r-help, r-devel.

Visit bigRR on R Graphical Manual.