Modeling Spatially Varying Coefficients
Description
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) ). The package and its
capabilities are described in (Dambon et al. (2021c)
).