Automatically creates separate regression models for different spatial
regions. The prediction surface is smoothed using a regional border smoothing
method. If regional models are continuous, the resulting prediction surface is
continuous across the spatial dimensions, even at region borders. Methodology
is described in Wagstaff and Bean (2023) <doi:10.32614/RJ-2023-004>.
| Version: |
0.3.1 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
graphics (≥ 4.1.0), methods (≥ 4.1.0), parallel (≥ 4.1.0), sf (≥ 1.0.0), stats (≥ 4.1.0), units (≥ 0.6.7), utils (≥
4.1.0) |
| Suggests: |
dplyr (≥ 1.0.2), ggplot2 (≥ 3.3.2), knitr (≥ 1.30), maps (≥ 3.3.0), mgcv (≥ 1.8.33), rmarkdown (≥ 2.5) |
| Published: |
2023-06-14 |
| DOI: |
10.32614/CRAN.package.remap |
| Author: |
Jadon Wagstaff [aut, cre],
Brennan Bean [aut] |
| Maintainer: |
Jadon Wagstaff <jadonw at gmail.com> |
| BugReports: |
https://github.com/jadonwagstaff/remap/issues |
| License: |
GPL-3 |
| URL: |
https://github.com/jadonwagstaff/remap |
| NeedsCompilation: |
no |
| Citation: |
remap citation info |
| Materials: |
NEWS |
| CRAN checks: |
remap results |