rrpack

Multivariate regression methodologies including classical reduced-rank regression (RRR) studied by Anderson (1951) doi:10.1214/aoms/1177729580 and Reinsel and Velu (1998) doi:10.1007/978-1-4757-2853-8, reduced-rank regression via adaptive nuclear norm penalization proposed by Chen et al. (2013) doi:10.1093/biomet/ast036 and Mukherjee et al. (2015) doi:10.1093/biomet/asx080, robust reduced-rank regression (R4) proposed by She and Chen (2017) doi:10.1093/biomet/asx032, generalized/mixed-response reduced-rank regression (mRRR) proposed by Luo et al. (2018) doi:10.1016/j.jmva.2018.04.011, row-sparse reduced-rank regression (SRRR) proposed by Chen and Huang (2012) doi:10.1080/01621459.2012.734178, reduced-rank regression with a sparse singular value decomposition (RSSVD) proposed by Chen et al. (2012) doi:10.1111/j.1467-9868.2011.01002.x and sparse and orthogonal factor regression (SOFAR) proposed by Uematsu et al. (2019) doi:10.1109/TIT.2019.2909889.

Last 30 days

This package has been downloaded 316 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 15 times.

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

Last 365 days

This package has been downloaded 3,314 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Jan 22, 2025 with 47 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.