Mapinguari: Process-Based Biogeographical Analysis

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>
License: GPL-2
NeedsCompilation: no
CRAN checks: Mapinguari results


Reference manual: Mapinguari.pdf


Package source: Mapinguari_2.0.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
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


Please use the canonical form to link to this page.