glmmrBase: Generalised Linear Mixed Models in R
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: |
0.11.1 |
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: |
2024-12-10 |
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 [issues need fixing before 2025-01-10] |
Documentation:
Downloads:
Reverse dependencies:
Linking:
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