Penalized Multivariate Analysis

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Documentation for package ‘PMA2’ version 2.1

• DESCRIPTION file.

Help Pages

PMA-package	Penalized Multivariate Analysis
breastdata	Breast cancer gene expression + DNA copy number data set from Chin et. al. and used in Witten, et. al. See references below.
CCA	Perform sparse canonical correlation analysis using the penalized matrix decomposition.
CCA.permute	Select tuning parameters for sparse canonical correlation analysis using the penalized matrix decomposition.
MultiCCA	Perform sparse multiple canonical correlation analysis.
MultiCCA.permute	Select tuning parameters for sparse multiple canonical correlation analysis using the penalized matrix decomposition.
plot.MultiCCA.permute	Select tuning parameters for sparse multiple canonical correlation analysis using the penalized matrix decomposition.
plot.SPC.cv	Perform cross-validation on sparse principal component analysis
PlotCGH	Plot CGH data
PMA	Penalized Multivariate Analysis
PMD	Get a penalized matrix decomposition for a data matrix.
PMD.cv	Do tuning parameter selection for PMD via cross-validation
print.CCA	Perform sparse canonical correlation analysis using the penalized matrix decomposition.
print.MultiCCA	Perform sparse multiple canonical correlation analysis.
print.MultiCCA.permute	Select tuning parameters for sparse multiple canonical correlation analysis using the penalized matrix decomposition.
print.SPC	Perform sparse principal component analysis
print.SPC.cv	Perform cross-validation on sparse principal component analysis
SPC	Perform sparse principal component analysis
SPC.cv	Perform cross-validation on sparse principal component analysis