Package: mmpca 2.0.4

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 et al. (2019) <doi:10.48550/arXiv.1911.04927>.

Authors:Jonatan Kallus [aut], Felix Held [ctb, cre]

mmpca_2.0.4.tar.gz
mmpca_2.0.4.zip(r-4.7)mmpca_2.0.4.zip(r-4.6)mmpca_2.0.4.zip(r-4.5)
mmpca_2.0.4.tgz(r-4.6-x86_64)mmpca_2.0.4.tgz(r-4.6-arm64)mmpca_2.0.4.tgz(r-4.5-x86_64)mmpca_2.0.4.tgz(r-4.5-arm64)
mmpca_2.0.4.tar.gz(r-4.7-arm64)mmpca_2.0.4.tar.gz(r-4.7-x86_64)mmpca_2.0.4.tar.gz(r-4.6-arm64)mmpca_2.0.4.tar.gz(r-4.6-x86_64)
mmpca_2.0.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
mmpca/json (API)
NEWS

# Install 'mmpca' in R:

install.packages('mmpca', repos = c('https://cyianor.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/cyianor/mmpca/issues

Uses libs:

gsl– GNU Scientific Library (GSL)
c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

On CRAN:

data-integration gsl cpp openmp

3.00 score 2 stars 243 downloads 1 exports 4 dependencies

Last updated from:2170f736f8. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	139
linux-devel-x86_64	OK	120
source / vignettes	OK	154
linux-release-arm64	OK	176
linux-release-x86_64	OK	131
macos-release-arm64	OK	140
macos-release-x86_64	OK	234
macos-oldrel-arm64	OK	101
macos-oldrel-x86_64	OK	279
windows-devel	OK	122
windows-release	OK	117
windows-oldrel	OK	115
wasm-release	OK	117