drrglm
Doubly Regularized Matrix-Variate Regression
The doubly regularized matrix-variate regression solves a low-rank-plus-sparse structure for matrix-variate generalized linear models through a weighted combination of nuclear-norm and L1-norm. The methodology implemented by this package is described in the paper "Doubly Regularized Matrix-Variate Regression", which has been tentatively accepted for publication but does not yet have a DOI or URL. A formal citation will be added in a future update once the final publication details are available.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.3.2 |
rolling linux/jammy R-4.5 | drrglm_0.3.2.tar.gz |
6.4 MiB |
0.3.2 |
rolling linux/noble R-4.5 | drrglm_0.3.2.tar.gz |
6.4 MiB |
0.3.2 |
rolling source/ R- | drrglm_0.3.2.tar.gz |
8.4 MiB |
0.3.2 |
latest linux/jammy R-4.5 | drrglm_0.3.2.tar.gz |
6.4 MiB |
0.3.2 |
latest linux/noble R-4.5 | drrglm_0.3.2.tar.gz |
6.4 MiB |
0.3.2 |
latest source/ R- | drrglm_0.3.2.tar.gz |
8.4 MiB |
0.3.2 |
2026-04-26 source/ R- | drrglm_0.3.2.tar.gz |
8.4 MiB |
0.3.2 |
2026-04-23 source/ R- | drrglm_0.3.2.tar.gz |
8.4 MiB |