superpc: Supervised principal components

Supervised principal components for regression and survival analsysis. Especially useful for high-dimnesional data, including microarray data.

Install the latest version of this package by entering the following in R:
install.packages("superpc")
AuthorEric Bair, R. Tibshirani
Date of publication2012-02-27 07:36:05
MaintainerRob Tibshirani <tibs@stanford.edu>
LicenseGPL-2
Version1.09
http://www-stat.stanford.edu/~tibs/superpc

View on CRAN

Functions

cor.func Man page
coxfunc Man page
coxscor Man page
coxstuff Man page
coxvar Man page
mysvd Man page
superpc.cv Man page
superpc.decorrelate Man page
superpc.fit.to.outcome Man page
superpc.listfeatures Man page
superpc.lrtest.curv Man page
superpc.plotcv Man page
superpc.plot.lrtest Man page
superpc.plotred.lrtest Man page
superpc.predict Man page
superpc.predictionplot Man page
superpc.predict.red Man page
superpc.predict.red.cv Man page
superpc.rainbowplot Man page
superpc.train Man page
superpc.xl.decorrelate Man page
superpc.xl.decorrelate.test Man page
superpc.xl.fit.to.clin Man page
superpc.xl.get.threshold.range Man page
superpc.xl.listgenes.compute Man page
superpc.xl.rainbowplot Man page

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.