Package: lmebayes
Type: Package
Title: Bayesian Linear Mixed-Effects Models via Two-Block Gibbs
        Sampling
Version: 0.1.0
Date: 2026-08-10
Authors@R: c(
    person("Kjell", "Nygren", role = c("aut", "cre"),
           email = "kjell.a.nygren@gmail.com"),
    person("The R Core Team", role = c("ctb", "cph"),
           comment = "R Mathlib sources, R stats modeling code, and derived/adapted routines"),
    person("The R Foundation", role = "cph",
           comment = "Portions of R Mathlib and R source code"),
    person("Ross", "Ihaka", role = c("ctb", "cph"),
           comment = "R Mathlib and original R modeling infrastructure"),
    person("Robert", "Gentleman", role = c("ctb", "cph"),
           comment = "Portions of R Mathlib"),
    person("Simon", "Davies", role = "ctb",
           comment = "Original R glm implementation"),
    person("Morten", "Welinder", role = c("ctb", "cph"),
           comment = "Portions of R Mathlib"),
    person("Martin", "Maechler", role = "ctb",
           comment = "Portions of R Mathlib")
    )
Description: Provides Bayesian linear and generalized linear
        mixed-effects model fitting with near-independent posterior
        samples. The main functions mirror the 'lme4' lmer() and
        glmer() interfaces (X/beta for fixed effects, Z/b for random
        effects, D for the random-effects covariance) while adding
        prior family specifications for Gaussian, Poisson, binomial,
        and Gamma models with log-concave likelihoods. Sampling uses
        efficient two-block Gibbs sampling procedures with parallel
        chains and theoretically driven stopping rules. Gibbs sampling
        engines are provided by the 'lmebayesCore' package.
License: GPL (>= 2)
URL: https://github.com/knygren/lmebayes
BugReports: https://github.com/knygren/lmebayes/issues
Imports: glmbayesCore (>= 0.6.0), lmebayesCore, glmbayes, stats, lme4,
        Rcpp (>= 1.1.1), RcppParallel, Rdpack (>= 0.11-0), opencltools
        (>= 0.8.0)
RdMacros: Rdpack
LinkingTo: Rcpp, RcppArmadillo, RcppParallel
Depends: MASS, R (>= 3.5.0)
Suggests: coda, ggplot2, bayesrules, bayestestR, glmmTMB, LearnBayes,
        testthat (>= 3.0.0), spelling, knitr, rmarkdown
VignetteBuilder: knitr
SystemRequirements: Optional OpenCL support. If available, GPU
        acceleration will be used; otherwise, computation runs on CPU.
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.3
Config/testthat/edition: 3
LazyData: true
Language: en-US
Config/pak/sysreqs: cmake make libicu-dev ocl-icd-opencl-dev
Repository: https://knygren.r-universe.dev
Date/Publication: 2026-10-02 21:37:46 UTC
RemoteUrl: https://github.com/knygren/lmebayes
RemoteRef: HEAD
RemoteSha: 9447cd81eadcaf1bf4ccfead81f07ba915de2c2d
NeedsCompilation: yes
Packaged: 2026-10-02 21:45:24 UTC; root
Author: Kjell Nygren [aut, cre],
  The R Core Team [ctb, cph] (R Mathlib sources, R stats modeling code,
    and derived/adapted routines),
  The R Foundation [cph] (Portions of R Mathlib and R source code),
  Ross Ihaka [ctb, cph] (R Mathlib and original R modeling
    infrastructure),
  Robert Gentleman [ctb, cph] (Portions of R Mathlib),
  Simon Davies [ctb] (Original R glm implementation),
  Morten Welinder [ctb, cph] (Portions of R Mathlib),
  Martin Maechler [ctb] (Portions of R Mathlib)
Maintainer: Kjell Nygren <kjell.a.nygren@gmail.com>