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) <doi:10.48550/arXiv.2106.02364>).
| Version: |
0.3.4 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
glmnet, lhs, methods, mlr, mlrMBO, optimParallel (≥ 0.8-1), ParamHelpers, pbapply, smoof, spam |
| Suggests: |
DiceKriging, knitr, lattice, latticeExtra, parallel, rmarkdown, sp, spData, testthat (≥ 3.0.0) |
| Published: |
2022-09-17 |
| DOI: |
10.32614/CRAN.package.varycoef |
| Author: |
Jakob A. Dambon 
[aut, cre],
Fabio Sigrist
[ctb],
Reinhard Furrer
[ctb] |
| Maintainer: |
Jakob A. Dambon <jakob.dambon at math.uzh.ch> |
| BugReports: |
https://github.com/jakobdambon/varycoef/issues |
| License: |
GPL-2 |
| URL: |
https://github.com/jakobdambon/varycoef |
| NeedsCompilation: |
no |
| Citation: |
varycoef citation info |
| In views: |
Spatial |
| CRAN checks: |
varycoef results |