Convenient model fitting using (iterated) INLA.
inlabru facilitates Bayesian spatial modeling using integrated nested Laplace approximations. It
is heavily based on R-inla (http://www.r-inla.org) but adds additional modeling abilities.
Tutorials and more information can be found at http://www.inlabru.org/.
The main function for inference using inlabru is bru. For point process inference lgcp is
a good starting point. The package comes with multiple real world data sets, namely gorillas,
mexdolphin, seals. Plotting these data sets is straight forward using inlabru's extensions
to ggplot2, e.g. the gg function. For educational purposes some simulated data sets are available
as well, e.g. Poisson1_1D, Poisson2_1D, Poisson2_1D and toygroups.