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.
- Version2.0.3
- R versionunknown
- LicenseGPL (≥ 3)
- Needs compilation?Yes
- Last release11/15/2022
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Team
Felix Held
Jonatan Kallus
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- Imports2 packages
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