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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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Version

Install

install.packages('superpc')

Monthly Downloads

6,450

Version

1.09

License

GPL-2

Maintainer

Rob Tibshirani

Last Published

February 27th, 2012

Functions in superpc (1.09)

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