Conducts hierarchical partitioning to calculate individual contributions of each fixed effects towards marginal R2 for generalized mixed-effect model based on output of r.squaredGLMM() in 'MuMIn', applying the algorithm of Lai J.,Zou Y., Zhang J.,Peres-Neto P.(2022) Generalizing hierarchical and variation partitioning in multiple regression and canonical analyses using the rdacca.hp R package.Methods in Ecology and Evolution,<DOI:10.1111/2041-210X.13800>.

Conducts hierarchical partitioning to calculate individual contributions of each fixed effects towards marginal R2 for generalized mixed-effect model based on output of r.squaredGLMM() in 'MuMIn', applying the algorithm of Lai J.,Zou Y., Zhang J.,Peres-Neto P.(2022) Generalizing hierarchical and variation partitioning in multiple regression and canonical analyses using the rdacca.hp R package.Methods in Ecology and Evolution,13:782-788<DOI:10.1111/2041-210X.13800>.

R (>= 2.10.0), smoothSurv, coda, mvtnorm

Generalised Linear Mixed Models with WinBUGS
works with R2WinBUGS, writing model files and dealing with unbalanced data

Generalised Linear Mixed Models and Spatial Models with BUGS
Write bugs model files for hierarchical and spatial models, arranges unbalanced data in ragged arrays, and creates starting values.

Write bugs model files for hierarchical and spatial
models, arranges unbalanced data in ragged arrays, and creates
starting values.

Generalised Linear Mixed Models and Spatial Models with WinBUGS,
BRugs, or OpenBUGS

R (>= 2.10), MASS, nlme, abind, spdep, RandomFields, raster

R2WinBUGS, R2OpenBUGS, BRugs, R2jags, sp, nlme

Generalised Linear Mixed Models with BUGS and JAGS
abind, methods, MASS, sp, graphics, stats
nlme, diseasemapping, geoRglm, R2WinBUGS, R2OpenBUGS, BRugs,
R2jags, rjags
Automates running Generalized Linear Mixed Models, including
spatial models, with WinBUGS, OpenBUGS and JAGS. Models are specified with
formulas, with the package writings model files, arranging unbalanced data
in ragged arrays, and creating starting values. The model is re-parameterized,
and functions are provided for converting model outputs to the original
parameterization.
Compiling vignette requires JAGS
(http://mcmc-jags.sourceforge.net)