Specification, analysis, simulation, and fitting of generalised linear mixed models. Includes Markov Chain Monte Carlo Maximum likelihood and Laplace approximation model fitting for a range of models, non-linear fixed effect specifications, a wide range of flexible covariance functions that can be combined arbitrarily, robust and bias-corrected standard error estimation, power calculation, data simulation, and more. See <https://samuel-watson.github.io/glmmr-web/> for a detailed manual.
Version: 1.0.1 Depends: R (≥ 3.5.0), Matrix (≥ 1.3-1) Imports: methods, Rcpp (≥ 1.0.11), R6, rstan (≥ 2.32.1), rstantools (≥ 2.3.1.1) LinkingTo: Rcpp (≥ 1.0.11), RcppEigen, SparseChol (≥ 0.3.2), BH, RcppParallel (≥ 5.0.1), rstan (≥ 2.32.1), StanHeaders (≥ 2.32.0) Published: 2025-07-08 DOI: 10.32614/CRAN.package.glmmrBase Author: Sam Watson [aut, cre] Maintainer: Sam Watson <S.I.Watson at bham.ac.uk> BugReports: https://github.com/samuel-watson/glmmrBase/issues License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] URL: https://github.com/samuel-watson/glmmrBase NeedsCompilation: yes SystemRequirements: GNU make Materials: README In views: MixedModels CRAN checks: glmmrBase results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=glmmrBase to link to this page.
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