PCDimension: Finding the Number of Significant Principal Components

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The PCDimension package implements two methods for determining the number of significant principal components.

Author
Kevin R. Coombes, Min Wang
Date of publication
2016-05-11 12:53:55
Maintainer
Kevin R. Coombes <krc@silicovore.com>
License
Apache License (== 2.0)
Version
1.1.3
URLs

View on R-Forge

Man pages

agfun
Divide Steps into "Long" and "Short" to Compute Auer-Gervini...
AuerGervini-class
Estimating Number of Principal Components Using the...
brokenStick
The Broken Stick Method
compare
Compare Methods to Divide Steps into "Long" and "Short"
rndLambdaF
Principal Component Statistics Based on Randomization
spca-data
Sample PCA Dataset

Files in this package

PCDimension/DESCRIPTION
PCDimension/NAMESPACE
PCDimension/NEWS
PCDimension/R
PCDimension/R/00-Auer-Gervini.R
PCDimension/TODO
PCDimension/data
PCDimension/data/spca.rda
PCDimension/man
PCDimension/man/AuerGervini-class.Rd
PCDimension/man/agfun.Rd
PCDimension/man/brokenStick.Rd
PCDimension/man/compare.Rd
PCDimension/man/rndLambdaF.Rd
PCDimension/man/spca-data.Rd
PCDimension/tests
PCDimension/tests/00-auer.R
PCDimension/tests/00-auer.Rout.save