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) doi:10.48550/arXiv.2101.09110.
- Version1.0
- R version≥ 3.1.0
- LicenseMIT
- Needs compilation?No
- Feng et al 2018
- Ponzi et al 2021
- Last release02/04/2021
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Team
Erica Ponzi
Abhik Ghosh
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- Imports3 packages
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