Mixed models, particularly spatial GLMMs
Description
Implements a collection of functions for inference in
hierarchical generalized linear models (HGLMs), which include GLMMs but also non-Gaussian random effects (e.g. Beta Binomial).
It was developed in particular for GLMMs with spatial correlations.
Heteroskedasticity can further be fitted by a linear model.
The algorithms are currently various Laplace approximations methods for ML or REML,
in particular h-likelihood and penalized-likelihood methods.