LOCUS

Low-Rank Decomposition of Brain Connectivity Matrices with Uniform Sparsity

CRAN Package

To decompose symmetric matrices such as brain connectivity matrices so that one can extract sparse latent component matrices and also estimate mixing coefficients, a blind source separation (BSS) method named LOCUS was proposed in Wang and Guo (2023) doi:10.48550/arXiv.2008.08915. For brain connectivity matrices, the outputs correspond to sparse latent connectivity traits and individual-level trait loadings.

  • Version1.0
  • R versionunknown
  • LicenseGPL-2
  • Needs compilation?No
  • Last release10/04/2022

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  • Depends3 packages