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: |
0.5.3 |
| Depends: |
R (≥ 3.5.0), Matrix (≥ 1.3-1) |
| Imports: |
methods, digest, Rcpp (≥ 1.0.11), R6 |
| LinkingTo: |
Rcpp (≥ 1.0.11), RcppEigen, SparseChol (≥ 0.2.2), BH, RcppParallel (≥ 5.0.1), rminqa (≥ 0.2.2) |
| Published: |
2023-11-24 |
| 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 |
| CRAN checks: |
glmmrBase results |
Documentation:
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