Carries out the kernelEVD algorithm for data reduction

Description

This step reduces the data space to the affine subspace spanned by the n observations.

Usage

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Arguments

x

A data matrix.

best

An optional subset of 1:n.

q

Desired rank of the SVD decomposition. Optional.

Value

A reduced data set with full rank.

Author(s)

Small modification of the code from the classPC from rrcov.

References

Wu, W., Massart, D. L., and de Jong, S. (1997), 'The Kernel PCA Algorithms for Wide Data. Part I: Theory and Algorithms,' Chemometrics and Intelligent Laboratory Systems,36,165–172

Examples

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n<-50
p<-200
x<-matrix(rnorm(n*p),nc=p)
W<-FHCSkernelEVD(x)