LOCUS

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.

Last 30 days

This package has been downloaded 150 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 6 times.

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Last 365 days

This package has been downloaded 1,928 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Sep 11, 2024 with 38 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.