mmpca: Integrative Analysis of Several Related Data Matrices

A generalization of principal component analysis for integrative analysis. The method finds principal components that describe single matrices or that are common to several matrices. The solutions are sparse. Rank of solutions is automatically selected using cross validation. The method is described in Kallus, Johansson, Nelander and J├Ârnsten (2019) <arXiv:1911.04927>.

Version: 1.0.2
Depends: R (≥ 3.3.0)
Imports: CMF (≥ 1.0), digest (≥ 0.6.0), gsl (≥ 1.9)
LinkingTo: Rcpp, RcppEigen
Published: 2019-12-05
Author: Jonatan Kallus [aut, cre]
Maintainer: Jonatan Kallus <kallus at chalmers.se>
License: GPL-3
NeedsCompilation: yes
CRAN checks: mmpca results

Downloads:

Reference manual: mmpca.pdf
Package source: mmpca_1.0.2.tar.gz
Windows binaries: r-devel: mmpca_1.0.2.zip, r-devel-gcc8: mmpca_1.0.2.zip, r-release: mmpca_1.0.2.zip, r-oldrel: mmpca_1.0.2.zip
OS X binaries: r-release: mmpca_1.0.2.tgz, r-oldrel: mmpca_1.0.2.tgz
Old sources: mmpca archive

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