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superpc (version 1.09)
Supervised principal components
Description
Supervised principal components for regression and survival analsysis. Especially useful for high-dimnesional data, including microarray data.
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Install
install.packages('superpc')
Monthly Downloads
3,230
Version
1.09
License
GPL-2
Maintainer
Rob Tibshirani
Last Published
February 27th, 2012
Functions in superpc (1.09)
Search functions
superpc.decorrelate
Decorrelate features with respect to competing predictors
superpc.plot.lrtest
Plot likelhiood ratio test statistics
superpc.plotred.lrtest
Plot likelihood ratio test statistics from supervised principal components predictor
superpc-internal
Internal superpc functions
superpc.rainbowplot
Make rainbow plot of superpc and compeiting predictors
superpc.predict.red
Feature selection for supervised principal components
superpc.predict.red.cv
Cross-validation of feature selection for supervised principal components
superpc.plotcv
Plot output from superpc.cv
superpc.predictionplot
Plot outcome predictions from superpc
superpc.predict
Form principal components predictor from a trained superpc object
superpc.fit.to.outcome
Fit predictive model using outcome of supervised principal components
superpc.listfeatures
Return a list of the important predictors
superpc.cv
Cross-validation for supervised principal components
superpc.lrtest.curv
Compute values of likelihood ratio test from supervised principal components fit
superpc.train
Prediction by supervised principal components