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: 0.3.2 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: 2025-01-09 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 Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=remap to link to this page.
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