Package: lmmprobe 0.1.0

lmmprobe: Sparse High-Dimensional Linear Mixed Modeling with a Partitioned Empirical Bayes ECM Algorithm

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.

Authors:Anja Zgodic [aut, cre], Ray Bai [aut], Jiajia Zhang [aut], Alex McLain [aut], Peter Olejua [aut]

lmmprobe_0.1.0.tar.gz
lmmprobe_0.1.0.zip(r-4.7-x86_64)lmmprobe_0.1.0.zip(r-4.7-arm64)lmmprobe_0.1.0.zip(r-4.6-x86_64)lmmprobe_0.1.0.zip(r-4.6-arm64)lmmprobe_0.1.0.zip(r-4.5-x86_64)
lmmprobe_0.1.0.tgz(r-4.6-x86_64)lmmprobe_0.1.0.tgz(r-4.6-arm64)lmmprobe_0.1.0.tgz(r-4.5-x86_64)lmmprobe_0.1.0.tgz(r-4.5-arm64)
lmmprobe_0.1.0.tar.gz(r-4.7-arm64)lmmprobe_0.1.0.tar.gz(r-4.7-x86_64)lmmprobe_0.1.0.tar.gz(r-4.6-arm64)lmmprobe_0.1.0.tar.gz(r-4.6-x86_64)
lmmprobe_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
lmmprobe/json (API)

# Install 'lmmprobe' in R:

install.packages('lmmprobe', repos = c('https://anjazgodic.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/anjazgodic/lmmprobe/issues

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

Datasets:

real_data - Systemic Lupus Erythematosus (SLE) Gene Expression Data

On CRAN:

openblas cpp openmp

4.18 score 1 stars 5 scripts 227 downloads 1 exports 21 dependencies

Last updated from:69fd867609. Checks:15 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	142
linux-devel-x86_64	OK	186
source / vignettes	OK	293
linux-release-arm64	OK	141
linux-release-x86_64	OK	164
macos-release-arm64	OK	133
macos-release-x86_64	OK	462
macos-oldrel-arm64	OK	145
macos-oldrel-x86_64	OK	411
windows-devel-arm64	OK	390
windows-devel-x86_64	OK	232
windows-release-arm64	OK	399
windows-release-x86_64	OK	175
windows-oldrel-x86_64	OK	160
wasm-release	OK	128

Exports:lmmprobe

Dependencies:boot codetools digest future future.apply globals lattice listenv lme4 MASS Matrix minqa nlme nloptr parallelly rbibutils Rcpp RcppArmadillo RcppEigen Rdpack reformulas

Introduction to lmmprobe

Introduction | Loading the Package | Simulating Data

Rendered fromlmmprobe-intro.Rmdusingknitr::rmarkdown

Last update: 2026-03-10
Started: 2026-02-26

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Sparse high-dimensional linear mixed modeling with PaRtitiOned empirical Bayes ECM (LMM-PROBE) algorithm.	lmmprobe
Systemic Lupus Erythematosus (SLE) Gene Expression Data	real_data SLE