Description Details References

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`

.

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.

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

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