Crandore Hub

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>.

Versions across snapshots

VersionRepositoryFileSize
2.0.4 rolling linux/jammy R-4.5 mmpca_2.0.4.tar.gz 161.6 KiB
2.0.4 rolling linux/noble R-4.5 mmpca_2.0.4.tar.gz 167.6 KiB
2.0.4 rolling source/ R- mmpca_2.0.4.tar.gz 19.6 KiB
2.0.4 latest linux/jammy R-4.5 mmpca_2.0.4.tar.gz 161.6 KiB
2.0.4 latest linux/noble R-4.5 mmpca_2.0.4.tar.gz 167.6 KiB
2.0.4 latest source/ R- mmpca_2.0.4.tar.gz 19.6 KiB
2.0.4 2026-04-26 source/ R- mmpca_2.0.4.tar.gz 19.6 KiB
2.0.4 2026-04-23 source/ R- mmpca_2.0.4.tar.gz 19.6 KiB
2.0.4 2026-04-09 windows/windows R-4.5 mmpca_2.0.4.zip 675.6 KiB
2.0.3 2025-04-20 source/ R- mmpca_2.0.3.tar.gz 18.8 KiB

Dependencies (latest)

Imports

LinkingTo