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glmmrOptim: Approximate Optimal Experimental Designs Using Generalised Linear Mixed Models

Optimal design analysis algorithms for any study design that can be represented or modelled as a generalised linear mixed model including cluster randomised trials, cohort studies, spatial and temporal epidemiological studies, and split-plot designs. See <https://github.com/samuel-watson/glmmrBase/blob/master/README.md> for a detailed manual on model specification. A detailed discussion of the methods in this package can be found in Watson, Hemming, and Girling (2023) <doi:10.1177/09622802231202379>.

Version: 0.3.5
Depends: R (≥ 3.4.0), Matrix, glmmrBase
Imports: methods, Rcpp (≥ 1.0.7), digest
LinkingTo: Rcpp (≥ 1.0.7), RcppEigen, RcppProgress, glmmrBase (≥ 0.4.6), SparseChol (≥ 0.2.1), BH, rminqa (≥ 0.2.2)
Suggests: testthat, CVXR
Published: 2024-06-02
DOI: 10.32614/CRAN.package.glmmrOptim
Author: Sam Watson [aut, cre], Yi Pan [aut]
Maintainer: Sam Watson <S.I.Watson at bham.ac.uk>
BugReports: https://github.com/samuel-watson/glmmrOptim/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/samuel-watson/glmmrOptim
NeedsCompilation: yes
SystemRequirements: GNU make
CRAN checks: glmmrOptim results

Documentation:

Reference manual: glmmrOptim.pdf

Downloads:

Package source: glmmrOptim_0.3.5.tar.gz
Windows binaries: r-devel: glmmrOptim_0.3.5.zip, r-release: glmmrOptim_0.3.5.zip, r-oldrel: glmmrOptim_0.3.5.zip
macOS binaries: r-release (arm64): glmmrOptim_0.3.5.tgz, r-oldrel (arm64): glmmrOptim_0.3.5.tgz, r-release (x86_64): glmmrOptim_0.3.5.tgz, r-oldrel (x86_64): glmmrOptim_0.3.5.tgz
Old sources: glmmrOptim archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=glmmrOptim to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.