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 gmail.com>
BugReports:	https://github.com/gabrielhoc/Mapinguari/issues
License:	GPL-2
URL:	https://github.com/gabrielhoc/Mapinguari
NeedsCompilation:	no
CRAN checks:	Mapinguari results

Documentation:

Reference manual:

Mapinguari.pdf

Downloads:

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

Linking:

Please use the canonical form https://CRAN.R-project.org/package=Mapinguari to link to this page.