Supervised Principal Components
Cross-validation for supervised principal components
Decorrelate features with respect to competing predictors
Fit predictive model using outcome of supervised principal components
Return a list of the important predictors
Compute values of likelihood ratio test from supervised principal comp...
Display the superpc Package News
Plot likelhiood ratio test statistics
Plot output from superpc.cv
Plot likelihood ratio test statistics from supervised principal compon...
Form principal components predictor from a trained superpc object
Cross-validation of feature selection for supervised principal compone...
Feature selection for supervised principal components
Plot outcome predictions from superpc
Make rainbow plot of superpc and compeiting predictors
Prediction by supervised principal components
Does prediction in the case of a censored survival outcome, or a regression outcome, using the "supervised principal component" approach. 'Superpc' is especially useful for high-dimensional data when the number of features p dominates the number of samples n (p >> n paradigm), as generated, for instance, by high-throughput technologies.