Package: RaJIVE 1.0

RaJIVE: Robust Angle Based Joint and Individual Variation Explained

A robust alternative to the aJIVE (angle based Joint and Individual Variation Explained) method (Feng et al 2018: <doi:10.1016/j.jmva.2018.03.008>) for the estimation of joint and individual components in the presence of outliers in multi-source data. It decomposes the multi-source data into joint, individual and residual (noise) contributions. The decomposition is robust to outliers and noise in the data. The method is illustrated in Ponzi et al (2021) <arxiv:2101.09110>.

Authors:Erica Ponzi [aut, cre], Abhik Ghosh [aut]

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RaJIVE.pdf |RaJIVE.html✨
RaJIVE/json (API)

# Install 'RaJIVE' in R:
install.packages('RaJIVE', repos = c('https://ericaponzi.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ericaponzi/rajive/issues

On CRAN:

2.70 score 1 scripts 195 downloads 8 exports 32 dependencies

Last updated 4 years agofrom:7d494d1102. Checks:8 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 03 2025
R-4.5-winOKFeb 03 2025
R-4.5-macOKFeb 03 2025
R-4.5-linuxOKFeb 03 2025
R-4.4-winOKFeb 03 2025
R-4.4-macOKFeb 03 2025
R-4.3-winOKFeb 03 2025
R-4.3-macOKFeb 03 2025

Exports:ajive.data.simdecomposition_heatmaps_robustHget_block_loadingsget_block_scoresget_individual_rankget_joint_rankRajiveshowVarExplained_robust

Dependencies:clicodetoolscolorspacedoParallelfansifarverforeachggplot2gluegtableisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr