Bayesian spatial models in INLA

Typically, the linear predictor contains both:

• (independent) linear covariate effects: \(X_i \cdot \beta\)
  These will typically correspond to the fixed effects of frequentist GLMMs.
• other covariate effects: \(Z_i\)
  E.g. non-linear effects, spatial, time & seasonal patterns, random intercepts & slope.