Corpus ID: 231693078

RaJIVE: Robust Angle Based JIVE for Integrating Noisy Multi-Source Data

@inproceedings{Ponzi2021RaJIVERA,
  title={RaJIVE: Robust Angle Based JIVE for Integrating Noisy Multi-Source Data},
  author={Erica Ponzi and M. Thoresen and A. Ghosh},
  year={2021}
}
Motivation: With increasing availability of high dimensional, multi-source data, the identification of joint and data specific patterns of variability has become a subject of interest in many research areas. Several matrix decomposition methods have been formulated for this purpose, for example JIVE (Joint and Individual Variation Explained), and its angle based variation, aJIVE. Although the effect of data contamination on the estimated joint and individual components has not been considered… Expand

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