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superpc
View on CRAN: Click
here
Download and install superpc package within the R console
Install from CRAN:
install.packages("superpc")
Install from Github:
library("remotes")
install_github("cran/superpc") Install by package version:
library("remotes")
install_version("superpc", "1.12") Attach the package and use:
library("superpc")
Maintained by
Jean-Eudes Dazard
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2004-09-16
Latest Update: 2020-10-19
Description:
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.
How to cite:
Jean-Eudes Dazard (2004). superpc: Supervised Principal Components. R package version 1.12, https://cran.r-project.org/web/packages/superpc. Accessed 09 Sep. 2026.
Previous versions and publish date:
Other packages that cited superpc R package
View superpc citation profile
Other R packages that superpc depends,
imports, suggests or enhances
Complete documentation for superpc
Functions, R codes and Examples using
the superpc R package
Some associated functions: superpc.cv . superpc.decorrelate . superpc.fit.to.outcome . superpc.listfeatures . superpc.lrtest.curv . superpc.news . superpc.plot.lrtest . superpc.plotcv . superpc.plotred.lrtest . superpc.predict . superpc.predict.red.cv . superpc.predict.red . superpc.predictionplot . superpc.rainbowplot . superpc.train .
Some associated R codes: balanced.folds.R . permute.rows.R . superpc.cv.R . superpc.decorrelate.R . superpc.fit.to.outcome.R . superpc.listfeatures.R . superpc.lrtest.curv.R . superpc.morefuns.R . superpc.news.R . superpc.plot.lrtest.R . superpc.plotcv.R . superpc.plotred.lrtest.R . superpc.predict.R . superpc.predict.red.R . superpc.predict.red.cv.R . superpc.predictionplot.R . superpc.rainbowplot.R . superpc.train.R . superpc.xlfuns.R . Full superpc package functions and examples
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