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 213 downloads 1 exports 4 dependencies

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

Target	Result	Time
linux-devel-arm64	OK	141
linux-devel-x86_64	OK	127
source / vignettes	OK	280
linux-release-arm64	OK	158
linux-release-x86_64	OK	125
macos-release-arm64	OK	108
macos-release-x86_64	OK	199
macos-oldrel-arm64	OK	96
macos-oldrel-x86_64	OK	255
windows-devel	OK	160
windows-release	OK	121
windows-oldrel	OK	124
wasm-release	OK	108