Type: Package
Package: IMR
Title: Incomplete Matrix Regression
Version: 1.0.0
Authors@R: c(
    person("Khaled", "Fouda", , "khaled.fouda@hec.ca", role = c("aut", "cre"),
           comment = c(ORCID = "0009-0000-3688-8767")),
    person("Aurélie", "Labbe", role = c("ths", "ctb")),
    person("Karim", "Oualkacha", role = c("ths", "ctb")),
    person("Korbinian", "Strimmer", role = c("cph", "ctb"),
           comment = "Authored original fast.svd R implementation in the corpcor package")
  )
Description: 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>.
License: GPL (>= 3)
URL: https://github.com/khaledfouda/IMR
BugReports: https://github.com/khaledfouda/IMR/issues
Depends: R (>= 3.5)
Imports: fields, irlba, MASS, Matrix, methods, parallel, Rcpp,
        RSpectra, stats, utils
Suggests: knitr, rmarkdown, spelling, testthat (>= 3.0.0)
LinkingTo: Rcpp, RcppArmadillo
VignetteBuilder: knitr
Config/roxygen2/version: 8.0.0
Config/testthat/edition: 3
Encoding: UTF-8
Language: en-US
LazyData: true
SystemRequirements: C++17
NeedsCompilation: yes
Packaged: 2026-07-02 16:16:40 UTC; khaledfouda
Author: 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)
Maintainer: Khaled Fouda <khaled.fouda@hec.ca>
Repository: CRAN
Date/Publication: 2026-07-10 18:20:02 UTC
Built: R 4.4.3; x86_64-apple-darwin20; 2026-07-10 20:30:40 UTC; unix
Archs: IMR.so.dSYM
