High-Performance Open-Source Archive
Facilitates the incorporation of biological processes in biogeographical analyses. It offers conveniences in fitting, comparing and extrapolating models of biological processes such as physiology and phenology. These spatial extrapolations can be informative by themselves, but also complement traditional correlative species distribution models, by mixing environmental and process-based predictors. Caetano et al (2020) <doi:10.1111/oik.07123>.
| Version: | 2.0.1 |
| Depends: | R (≥ 3.5) |
| Imports: | dplyr, magrittr, parallel, raster, rlang, stringr, testthat |
| Suggests: | geosphere, mgcv |
| Published: | 2023-06-26 |
| DOI: | 10.32614/CRAN.package.Mapinguari |
| Author: | Gabriel Caetano [aut, cre], Juan Santos [aut], Barry Sinervo [aut] |
| Maintainer: | Gabriel Caetano <gabrielhoc at gmail.com> |
| BugReports: | https://github.com/gabrielhoc/Mapinguari/issues |
| License: | GPL-2 |
| URL: | https://github.com/gabrielhoc/Mapinguari |
| NeedsCompilation: | no |
| CRAN checks: | Mapinguari results |
| Reference manual: | Mapinguari.html , Mapinguari.pdf |
| Package source: | Mapinguari_2.0.1.tar.gz |
| Windows binaries: | r-devel: Mapinguari_2.0.1.zip, r-release: Mapinguari_2.0.1.zip, r-oldrel: Mapinguari_2.0.1.zip |
| macOS binaries: | r-release (arm64): Mapinguari_2.0.1.tgz, r-oldrel (arm64): Mapinguari_2.0.1.tgz, r-release (x86_64): Mapinguari_2.0.1.tgz, r-oldrel (x86_64): Mapinguari_2.0.1.tgz |
| Old sources: | Mapinguari archive |
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