Sparse PC by iterative SVD and soft-thresholding

`arrayspc(x,K=1,para,use.corr=FALSE, max.iter=200,trace=FALSE,eps=1e-3)`

x

The microarray matrix.

K

Number of components. Default is 1.

para

The thresholding parameters. A vector of length K.

use.corr

Perform PCA on the correlation matrix? This option is only effective when the argument type is set "data".

max.iter

Maximum number of iterations.

trace

If TRUE, prints out its progress.

eps

Convergence criterion.

A "arrayspc" object is returned.

The function is equivalent to a special case of spca() with the quadratic penalty=infinity. It is specifically designed for the case p>>n, like microarrays.

Zou, H., Hastie, T. and Tibshirani, R. (2006) "Sparse principal component
analysis" *Journal of Computational and Graphical Statistics*, 15 (2), 265--286.

spca, princomp