  Statistical analyses proceed by an iterative process of model fitting and
checking. The R-INLA package facilitates this iteration by fitting many
Bayesian models much faster than alternative MCMC approaches. As the
interpretation of results and model objects from Bayesian analyses can be
complex, the R package INLAutils provides users with easily accessible, clear
and customisable graphical summaries of model outputs from R- INLA.
Furthermore, it offers a function for performing and visualizing the results of
a spatial leave-one-out cross-validation (SLOOCV) approach that can be applied
to compare the predictive performance of multiple spatial models. In this
paper, we describe and illustrate the use of (1) graphical summary plotting
functions and (2) the SLOOCV approach. We conclude the paper by identifying the
limits of our approach and discuss future potential improvements.
