Package: LOCUS
Type: Package
Title: Low-Rank Decomposition of Brain Connectivity Matrices with
        Uniform Sparsity
Version: 1.0
Date: 2022-08-28
Authors@R: c(person("Yikai", "Wang", role = c("aut", "cph")), person("Jialu", "Ran", role = c("aut", "cre"), email = "jialuran422@gmail.com"), person("Ying", "Guo", role = c("aut", "ths")))
Maintainer: Jialu Ran <jialuran422@gmail.com>
Depends: R (>= 3.1.0), ica, MASS, far
Description: 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) <arXiv:2008.08915>. For brain connectivity matrices, the outputs correspond to sparse latent connectivity traits and individual-level trait loadings. 
License: GPL-2
NeedsCompilation: no
Packaged: 2022-09-15 14:18:07 UTC; scarlett
Author: Yikai Wang [aut, cph],
  Jialu Ran [aut, cre],
  Ying Guo [aut, ths]
Repository: CRAN
Date/Publication: 2022-10-04 07:20:05 UTC
Built: R 4.6.0; ; 2026-04-26 01:05:47 UTC; unix
