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lmmprobe  

Sparse High-Dimensional Linear Mixed Modeling with a Partitioned Empirical Bayes ECM Algorithm
View on CRAN: Click here


Download and install lmmprobe package within the R console
Install from CRAN:
install.packages("lmmprobe")

Install from Github:
library("remotes")
install_github("cran/lmmprobe")

Install by package version:
library("remotes")
install_version("lmmprobe", "0.1.0")



Attach the package and use:
library("lmmprobe")
Maintained by
Anja Zgodic
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-03-12
Latest Update: 2026-03-12
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) <doi:10.1007/s11222-025-10649-z>. The package provides efficient estimation and inference for mixed models with high-dimensional fixed effects.
How to cite:
Anja Zgodic (2026). lmmprobe: Sparse High-Dimensional Linear Mixed Modeling with a Partitioned Empirical Bayes ECM Algorithm. R package version 0.1.0, https://cran.r-project.org/web/packages/lmmprobe. Accessed 24 Oct. 2026.
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