varycoef: 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) <doi:10.1016/j.spasta.2020.100470>). Covariance tapering (Furrer et al. (2006) <doi:10.1198/106186006X132178>) 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) <doi:10.1080/13658816.2022.2097684>). The package and its capabilities are described in (Dambon et al. (2021c) <arXiv:2106.02364>).

Package details

AuthorJakob A. Dambon [aut, cre] (<>), Fabio Sigrist [ctb] (<>), Reinhard Furrer [ctb] (<>)
MaintainerJakob A. Dambon <>
Package repositoryView on CRAN
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varycoef documentation built on Sept. 18, 2022, 1:07 a.m.