robustlmm: Robust Linear Mixed Effects Models

A method to fit linear mixed effects models robustly. Robustness is achieved by modification of the scoring equations combined with the Design Adaptive Scale approach.

Version: 2.4-5
Depends: lme4 (≥ 1.1-9), Matrix (≥ 1.0-13), R (≥ 3.2.0)
Imports: ggplot2, lattice, nlme, methods, robustbase (≥ 0.93), xtable, Rcpp (≥ 0.12.2), fastGHQuad
LinkingTo: Rcpp, RcppEigen, robustbase, cubature (> 1.3-8)
Suggests: digest, reshape2, microbenchmark, emmeans (≥ 1.4), estimability
Published: 2021-10-06
Author: Manuel Koller
Maintainer: Manuel Koller <koller.manuel at gmail.com>
License: GPL-2
URL: https://github.com/kollerma/robustlmm
NeedsCompilation: yes
SystemRequirements: C++11
Citation: robustlmm citation info
Materials: README
In views: Robust
CRAN checks: robustlmm results

Documentation:

Reference manual: robustlmm.pdf
Vignettes: robustlmm: An R Package for Robust Estimation of Linear Mixed-Effects Models

Downloads:

Package source: robustlmm_2.4-5.tar.gz
Windows binaries: r-devel: robustlmm_2.4-5.zip, r-devel-UCRT: robustlmm_2.4-5.zip, r-release: robustlmm_2.4-5.zip, r-oldrel: robustlmm_2.4-5.zip
macOS binaries: r-release (arm64): robustlmm_2.4-4.tgz, r-release (x86_64): robustlmm_2.4-5.tgz, r-oldrel: robustlmm_2.4-5.tgz
Old sources: robustlmm archive

Reverse dependencies:

Reverse suggests: effects, insight, qra

Linking:

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