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>.
| Version: |
1.0.0 |
| Depends: |
R (≥ 3.5) |
| Imports: |
fields, irlba, MASS, Matrix, methods, parallel, Rcpp, RSpectra, stats, utils |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
knitr, rmarkdown, spelling, testthat (≥ 3.0.0) |
| Published: |
2026-07-10 |
| DOI: |
10.32614/CRAN.package.IMR (may not be active yet) |
| Author: |
Khaled Fouda 
[aut, cre],
Aurélie Labbe [ths, ctb],
Karim Oualkacha [ths, ctb],
Korbinian Strimmer [cph, ctb] (Authored original fast.svd R
implementation in the corpcor package) |
| Maintainer: |
Khaled Fouda <khaled.fouda at hec.ca> |
| BugReports: |
https://github.com/khaledfouda/IMR/issues |
| License: |
GPL (≥ 3) |
| URL: |
https://github.com/khaledfouda/IMR |
| NeedsCompilation: |
yes |
| SystemRequirements: |
C++17 |
| Language: |
en-US |
| Citation: |
IMR citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
IMR results |