Modeling Spatially Varying Coefficients
Implements a maximum likelihood estimation (MLE)
method for estimation and prediction of Gaussian process-based
spatially varying coefficient (SVC) models
(Dambon et al. (2021a) ).
Covariance tapering (Furrer et al. (2006) ) can
be applied such that the method scales to large data. Further, it implements
a joint variable selection of the fixed and random effects (Dambon et al.
(2021b) ).