Provides methods for linear regression in the presence of missing data, including missingness in covariates and responses. The package implements two estimators: oss_estimator(), a low-dimensional semi-supervised method, and dantzig_missing(), a high-dimensional approach. The tuning parameter can be selected automatically via cv_dantzig_missing(). See Risebrow and Berrett (2026) <doi:10.48550/arXiv.2602.13729>. Optional support for the 'gurobi' optimizer via the 'gurobi' R package (available from Gurobi, see <https://docs.gurobi.com/projects/optimizer/en/current/reference/r.html>).
| Version: | 0.0.1 |
| Imports: | MASS, stats, Rglpk, fastDummies, Rdpack |
| Suggests: | gurobi |
| Published: | 2026-02-20 |
| DOI: | 10.32614/CRAN.package.LRMiss |
| Author: | Benedict Risebrow [aut, cre], Thomas Berrett [aut] |
| Maintainer: | Benedict Risebrow <Benedict.risebrow at warwick.ac.uk> |
| BugReports: | https://github.com/benrisebrow/LRMiss/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/benrisebrow/LRMiss |
| NeedsCompilation: | no |
| CRAN checks: | LRMiss results |
| Reference manual: | LRMiss.html , LRMiss.pdf |
| Package source: | LRMiss_0.0.1.tar.gz |
| Windows binaries: | r-devel: LRMiss_0.0.1.zip, r-release: LRMiss_0.0.1.zip, r-oldrel: LRMiss_0.0.1.zip |
| macOS binaries: | r-release (arm64): LRMiss_0.0.1.tgz, r-oldrel (arm64): LRMiss_0.0.1.tgz, r-release (x86_64): LRMiss_0.0.1.tgz, r-oldrel (x86_64): LRMiss_0.0.1.tgz |
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