Incomplete Matrix Regression R package IMR version 1.0.0 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>. Software 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) Khaled Fouda <khaled.fouda@hec.ca> Comprehensive R Archive Network (CRAN) Khaled Fouda [aut, cre] (ORCID: <https://orcid.org/0009-0000-3688-8767>), Aurélie Labbe [ths, ctb], Karim Oualkacha [ths, ctb], Korbinian Strimmer [cph, ctb] (Authored original fast.svd R implementation in the corpcor package) GPL (>= 3) 2026-07-10 application/tgz https://CRAN.R-project.org/package=IMR doi:10.32614/CRAN.package.IMR en-US