R: Penalized Multivariate Analysis

PMA-package {PMA} | R Documentation

## Penalized Multivariate Analysis

### Description

This package is called PMA, for __P__enalized __M__ultivariate __A__nalysis. It implements three methods: A penalized matrix decomposition, sparse principal components analysis, and sparse canonical correlations analysis. All are described in the reference below. The main functions are: `PMD`, `CCA` and `SPC`.

### Details

The first, `PMD`, performs a penalized matrix decomposition. `CCA` performs sparse canonical correlation analysis. `SPC` performs sparse principal components analysis.

There also are cross-validation functions for tuning parameter selection for each of the above methods: `SPC.cv`, `PMD.cv`, `CCA.permute`. And `PlotCGH` produces nice plots for DNA copy number data.

### References

Witten D. M., Tibshirani R., and Hastie, T. (2009) doi: 10.1093/biostatistics/kxp008.

[Package PMA version 1.2.1 Index]