  We compare two ways of constructing confidence intervals for the
moments-matching parameter estimates of a Gaussian spatio-temporal
Ornstein-Uhlenbeck process. It was found that those obtained via pairwise
likelihood approximations had lower coverages and were more prone to the curse
of dimensionality as opposed to those from a parametric bootstrap procedure.
