# PMA v1.2.1

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## Penalized Multivariate Analysis

Performs Penalized Multivariate Analysis: a penalized matrix decomposition, sparse principal components analysis, and sparse canonical correlation analysis, described in Witten, Tibshirani and Hastie (2009) <doi:10.1093/biostatistics/kxp008> and Witten and Tibshirani (2009) Extensions of sparse canonical correlation analysis, with applications to genomic data <doi:10.2202/1544-6115.1470>.

# PMA

Penalized Multivariate Analysis

## Functions in PMA

 Name Description PlotCGH Plot CGH data MultiCCA.permute Select tuning parameters for sparse multiple canonical correlation analysis using the penalized matrix decomposition. SPC.cv Perform cross-validation on sparse principal component analysis PMD Get a penalized matrix decomposition for a data matrix. SPC Perform sparse principal component analysis PMA-package Penalized Multivariate Analysis MultiCCA Perform sparse multiple canonical correlation analysis. PMD.cv Do tuning parameter selection for PMD via cross-validation 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. breastdata Breast cancer gene expression + DNA copy number data set from Chin et. al. and used in Witten, et. al. See references below. No Results!