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.