# arrayspc

From elasticnet v1.02
by Hui Zou

##### Sparse PCs of Microarrays

Sparse PC by iterative SVD and soft-thresholding

- Keywords
- multivariate

##### Usage

`arrayspc(x,K=1,para,use.corr=FALSE, max.iter=100,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.

##### References

Zou, H., Hastie, T. and Tibshirani, R. (2004) "Sparse principal component
analysis" *Technical report, Statistics Dept. Stanford University*

##### See Also

spca, princomp

*Documentation reproduced from package elasticnet, version 1.02, License: GPL version 2 or newer*

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