IMR
Incomplete Matrix Regression
A framework for matrix completion and regression on response matrices with missing values. The model estimates missing entries using any combination of intercepts, row and column covariates, and a low-rank matrix approximation. It applies Lasso penalties on the covariates and a nuclear norm penalty on the low-rank component. It also adjusts for correlation within the rows and columns of the target matrix using similarity matrices. The framework is described in Fouda, Labbe and Oualkacha (2026) <doi:10.48550/arXiv.2606.26325>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.0 |
rolling linux/jammy R-4.5 | IMR_1.0.0.tar.gz |
503.8 KiB |
1.0.0 |
rolling linux/noble R-4.5 | IMR_1.0.0.tar.gz |
506.9 KiB |
1.0.0 |
rolling source/ R- | IMR_1.0.0.tar.gz |
599.0 KiB |
1.0.0 |
latest linux/jammy R-4.5 | IMR_1.0.0.tar.gz |
503.8 KiB |
1.0.0 |
latest linux/noble R-4.5 | IMR_1.0.0.tar.gz |
506.9 KiB |
1.0.0 |
latest source/ R- | IMR_1.0.0.tar.gz |
599.0 KiB |
1.0.0 |
2026-04-23 source/ R- | IMR_1.0.0.tar.gz |
0 B |