xrnet

Fits hierarchical regularized regression models to incorporate potentially informative external data, Weaver and Lewinger (2019) doi:10.21105/joss.01761. Utilizes coordinate descent to efficiently fit regularized regression models both with and without external information with the most common penalties used in practice (i.e. ridge, lasso, elastic net). Support for standard R matrices, sparse matrices and big.matrix objects.

Last 30 days

This package has been downloaded 127 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 1 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 2,012 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 25, 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.