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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>).
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Package details |
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| Author | Jakob A. Dambon [aut, cre] (<https://orcid.org/0000-0001-5855-2017>), Fabio Sigrist [ctb] (<https://orcid.org/0000-0002-3994-2244>), Reinhard Furrer [ctb] (<https://orcid.org/0000-0002-6319-2332>) |
| Maintainer | Jakob A. Dambon <jakob.dambon@math.uzh.ch> |
| License | GPL-2 |
| Version | 0.3.4 |
| URL | https://github.com/jakobdambon/varycoef |
| Package repository | View on CRAN |
| Installation |
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