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:
RaJIVE_1.0.tar.gz
RaJIVE_1.0.zip(r-4.5)RaJIVE_1.0.zip(r-4.4)RaJIVE_1.0.zip(r-4.3)
RaJIVE_1.0.tgz(r-4.4-any)RaJIVE_1.0.tgz(r-4.3-any)
RaJIVE_1.0.tar.gz(r-4.5-noble)RaJIVE_1.0.tar.gz(r-4.4-noble)
RaJIVE_1.0.tgz(r-4.4-emscripten)RaJIVE_1.0.tgz(r-4.3-emscripten)
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
Last updated 4 years agofrom:7d494d1102. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 05 2024 |
| R-4.5-win | OK | Nov 05 2024 |
| R-4.5-linux | OK | Nov 05 2024 |
| R-4.4-win | OK | Nov 05 2024 |
| R-4.4-mac | OK | Nov 05 2024 |
| R-4.3-win | OK | Nov 05 2024 |
| R-4.3-mac | OK | Nov 05 2024 |
Exports:ajive.data.simdecomposition_heatmaps_robustHget_block_loadingsget_block_scoresget_individual_rankget_joint_rankRajiveshowVarExplained_robust
Dependencies:clicodetoolscolorspacedoParallelfansifarverforeachggplot2gluegtableisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr
