Sparse PC by iterative SVD and soft-thresholding
arrayspc(x,K=1,para,use.corr=FALSE, max.iter=200,trace=FALSE,eps=1e-3)The microarray matrix.
Number of components. Default is 1.
The thresholding parameters. A vector of length K.
Perform PCA on the correlation matrix? This option is only effective when the argument type is set "data".
Maximum number of iterations.
If TRUE, prints out its progress.
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