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LOCUS  

Low-Rank Decomposition of Brain Connectivity Matrices with Uniform Sparsity
View on CRAN: Click here


Download and install LOCUS package within the R console
Install from CRAN:
install.packages("LOCUS")

Install from Github:
library("remotes")
install_github("cran/LOCUS")

Install by package version:
library("remotes")
install_version("LOCUS", "1.0")



Attach the package and use:
library("LOCUS")
Maintained by
Jialu Ran
[Scholar Profile | Author Map]
First Published: 2022-10-04
Latest Update: 2022-10-04
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) . For brain connectivity matrices, the outputs correspond to sparse latent connectivity traits and individual-level trait loadings.
How to cite:
Jialu Ran (2022). LOCUS: Low-Rank Decomposition of Brain Connectivity Matrices with Uniform Sparsity. R package version 1.0, https://cran.r-project.org/web/packages/LOCUS. Accessed 01 May. 2025.
Previous versions and publish date:
No previous versions
Other packages that cited LOCUS R package
View LOCUS citation profile
Other R packages that LOCUS depends, imports, suggests or enhances
Complete documentation for LOCUS
Functions, R codes and Examples using the LOCUS R package
Some associated functions: LOCUS . LOCUS_BIC_selection . Ltrans . Ltrinv . 
Some associated R codes: LOCUS.R . LOCUS_BIC_selection.R . LOCUS_internal_in_bic.R . Locus_initial.R . Locus_preprocess.R . Locus_update.R . Locus_update_approx.R . Ltrans.R . Ltrinv.R . SCAD_func.R . calculate_bic.R . psdmat_inverse.R .  Full LOCUS package functions and examples
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