FastHCS (version 0.0.7)

FHCSkernelEVD: 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

FHCSkernelEVD(x,best=NULL,q=NULL)

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.

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

# NOT RUN {
n<-50
p<-200
x<-matrix(rnorm(n*p),nc=p)
W<-FHCSkernelEVD(x)
# }