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PMA  

Penalized Multivariate Analysis
View on CRAN: Click here


Download and install PMA package within the R console
Install from CRAN:
install.packages("PMA")

Install from Github:
library("remotes")
install_github("cran/PMA")

Install by package version:
library("remotes")
install_version("PMA", "1.2-4")



Attach the package and use:
library("PMA")
Maintained by
Balasubramanian Narasimhan
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2009-02-12
Latest Update: 2024-09-03
Description:
Performs Penalized Multivariate Analysis: a penalized matrix decomposition, sparse principal components analysis, and sparse canonical correlation analysis, described in Witten, Tibshirani and Hastie (2009) and Witten and Tibshirani (2009) Extensions of sparse canonical correlation analysis, with applications to genomic data .
How to cite:
Balasubramanian Narasimhan (2009). PMA: Penalized Multivariate Analysis. R package version 1.2-4, https://cran.r-project.org/web/packages/PMA. Accessed 30 Oct. 2026.
Previous versions and publish date:
(2026-07-09 08:16), 1.0.1 (2009-02-16 08:49), 1.0.2 (2009-04-15 09:33), 1.0.4 (2009-10-23 17:21), 1.0.5 (2009-12-06 11:08), 1.0.6 (2010-04-22 08:20), 1.0.7.1 (2011-02-06 11:36), 1.0.7 (2010-05-16 18:15), 1.0.8 (2011-08-11 19:34), 1.0.9 (2013-03-25 08:26), 1.0.10 (2018-04-20 09:03), 1.0.11 (2018-04-20 09:47), 1.0 (2009-02-12 09:25), 1.1 (2019-02-05 10:20), 1.2-2 (2023-07-20 23:20), 1.2-3 (2024-02-07 00:10), 1.2.1 (2020-02-03 18:30), 1.2 (2020-01-16 14:10)
Other packages that cited PMA R package
View PMA citation profile
Other R packages that PMA depends, imports, suggests or enhances
Complete documentation for PMA
Functions, R codes and Examples using the PMA R package
Some associated functions: CCA . CCA.permute . MultiCCA . MultiCCA.permute . PMA-package . PMD.cv . PMD . PlotCGH . SPC.cv . SPC . breastdata . 
Some associated R codes: CCA.R . FLSAGeneralInclude.R . MultiCCA.R . PMA-package.R . PMD.CGH.R . PMD.R . PlotFusedLasso.R . SamrFunctions.R . zzz.R .  Full PMA package functions and examples
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