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 Jörnsten (2019) <arXiv:1911.04927>.
| Version: | 2.0.1 |
| Depends: | R (≥ 3.3.0) |
| Imports: | digest (≥ 0.6.0), gsl (≥ 1.9) |
| LinkingTo: | Rcpp, RcppEigen |
| Published: | 2020-03-20 |
| Author: | Jonatan Kallus [aut, cre] |
| Maintainer: | Jonatan Kallus <kallus at chalmers.se> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| CRAN checks: | mmpca results |
| Reference manual: | mmpca.pdf |
| Package source: | mmpca_2.0.1.tar.gz |
| Windows binaries: | r-devel: mmpca_2.0.1.zip, r-release: mmpca_2.0.1.zip, r-oldrel: mmpca_2.0.1.zip |
| macOS binaries: | r-release: mmpca_2.0.1.tgz, r-oldrel: mmpca_2.0.1.tgz |
| Old sources: | mmpca archive |
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