arrayspc: Sparse PCs of Microarrays

Description Usage Arguments Details Value Author(s) References See Also

View source: R/enet_funcs.R

Description

Sparse PC by iterative SVD and soft-thresholding

Usage

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

Arguments

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.

Details

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.

Value

A "arrayspc" object is returned.

Author(s)

Hui Zou and Trevor Hastie

References

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

See Also

spca, princomp


elasticnet documentation built on July 1, 2020, 11:48 p.m.