Mixed-Effect Models, Particularly Spatial Models
Description
Inference in mixed-effect models, including generalized linear mixed models with spatial
correlations and models with non-Gaussian random effects (e.g., Beta Binomial,
or negative-binomial mixed models). Variation in residual variance is handled and can be modelled
as a linear model. The algorithms are currently various Laplace approximations
methods for likelihood or restricted likelihood, in particular h-likelihood and penalized-likelihood
methods.