Package: mmpca 2.0.3

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) <arxiv:1911.04927>.

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

mmpca_2.0.3.tar.gz
mmpca_2.0.3.zip(r-4.5)mmpca_2.0.3.zip(r-4.4)mmpca_2.0.3.zip(r-4.3)
mmpca_2.0.3.tgz(r-4.5-x86_64)mmpca_2.0.3.tgz(r-4.5-arm64)mmpca_2.0.3.tgz(r-4.4-x86_64)mmpca_2.0.3.tgz(r-4.4-arm64)mmpca_2.0.3.tgz(r-4.3-x86_64)mmpca_2.0.3.tgz(r-4.3-arm64)
mmpca_2.0.3.tar.gz(r-4.5-noble)mmpca_2.0.3.tar.gz(r-4.4-noble)
mmpca_2.0.3.tgz(r-4.4-emscripten)mmpca_2.0.3.tgz(r-4.3-emscripten)
mmpca.pdf |mmpca.html✨
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:

Conda:

data-integrationgslcppopenmp

3.00 score 2 stars 268 downloads 1 exports 4 dependencies

Last updated 1 months agofrom:a1124768a5. Checks:11 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 23 2025
R-4.5-win-x86_64OKFeb 23 2025
R-4.5-mac-x86_64OKFeb 23 2025
R-4.5-mac-aarch64OKFeb 23 2025
R-4.5-linux-x86_64OKFeb 23 2025
R-4.4-win-x86_64OKFeb 23 2025
R-4.4-mac-x86_64OKFeb 23 2025
R-4.4-mac-aarch64OKFeb 23 2025
R-4.3-win-x86_64OKFeb 23 2025
R-4.3-mac-x86_64OKFeb 23 2025
R-4.3-mac-aarch64OKFeb 23 2025

Exports:mmpca

Dependencies:digestRcppRcppEigenRcppGSL