Package: lmmprobe Type: Package Title: Sparse High-Dimensional Linear Mixed Modeling with a Partitioned Empirical Bayes ECM Algorithm Version: 0.1.0 Date: 2026-02-27 Authors@R: c(person(given = "Anja", family = "Zgodic", role = c("aut", "cre"), email = "anja.zgodic@gmail.com"), person(given = "Ray", family = "Bai", role = "aut", comment = c(ORCID = "0000-0001-7150-7229")), person(given = "Jiajia", family = "Zhang", role = "aut", comment = c(ORCID = "0000-0001-8281-8532")), person(given = "Alex", family = "McLain", role = "aut", comment = c(ORCID = "0000-0002-5475-0670")), person(given = "Peter", family = "Olejua", role = "aut", comment = c(ORCID = "0000-0002-2478-0908"))) Description: Implements a partitioned Empirical Bayes Expectation Conditional Maximization (ECM) algorithm for sparse high-dimensional linear mixed modeling as described in Zgodic, Bai, Zhang, and McLain (2025) . The package provides efficient estimation and inference for mixed models with high-dimensional fixed effects. License: GPL (>= 2) URL: https://github.com/anjazgodic/lmmprobe BugReports: https://github.com/anjazgodic/lmmprobe/issues Encoding: UTF-8 RoxygenNote: 7.3.3 Depends: R (>= 3.5.0) Imports: Rcpp (>= 1.0.8.3), lme4 (>= 1.1-29), future.apply (>= 1.10.0) LinkingTo: Rcpp, RcppArmadillo Suggests: testthat (>= 3.0.0), knitr, rmarkdown, MASS VignetteBuilder: knitr NeedsCompilation: yes Packaged: 2026-10-12 11:09:04 UTC; root Author: Anja Zgodic [aut, cre], Ray Bai [aut] (ORCID: ), Jiajia Zhang [aut] (ORCID: ), Alex McLain [aut] (ORCID: ), Peter Olejua [aut] (ORCID: ) Maintainer: Anja Zgodic Repository: https://cran.r-universe.dev Date/Publication: 2026-03-12 09:00:09 UTC RemoteUrl: https://github.com/cran/lmmprobe RemoteRef: HEAD RemoteSha: cbdfa860d269375cabd357b6c67cd06123d01e56