Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!
Get Started for Free

arrayspc

Sparse PCs of Microarrays


Description

Sparse PC by iterative SVD and soft-thresholding

Usage

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

Elastic-Net for Sparse Estimation and Sparse PCA

v1.3
GPL (>= 2)
Authors
Hui Zou <zouxx019@umn.edu> and Trevor Hastie <hastie@stanford.edu>
Initial release
2020-05-15

We don't support your browser anymore

Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.