SESraster: Raster Randomization for Null Hypothesis Testing

Randomization of presence/absence species distribution raster data with or without including spatial structure for calculating standardized effect sizes and testing null hypothesis. The randomization algorithms are based on classical algorithms for matrices (Gotelli 2000, <doi:10.2307/177478>) implemented for raster data.

Version: 0.7.0
Depends: R (≥ 2.10)
Imports: graphics, methods, rlang, stats, terra, utils
Suggests: kableExtra, knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2023-08-10
DOI: NA
Author: Neander Marcel Heming ORCID iD [aut, cre, cph], Flávio M. M. Mota ORCID iD [aut], Gabriela Alves-Ferreira ORCID iD [aut]
Maintainer: Neander Marcel Heming <neanderh at yahoo.com.br>
BugReports: https://github.com/HemingNM/SESraster/issues
License: GPL (≥ 3)
URL: https://CRAN.R-project.org/package=SESraster, https://github.com/HemingNM/SESraster, https://hemingnm.github.io/SESraster/
NeedsCompilation: no
Citation: SESraster citation info
Materials: README NEWS
CRAN checks: SESraster results

Documentation:

Reference manual: SESraster.pdf
Vignettes: Standardized effect sizes
Null model algorithms
Spatial null model algorithms in SESraster

Downloads:

Package source: SESraster_0.7.0.tar.gz
Windows binaries: r-devel: SESraster_0.7.0.zip, r-release: SESraster_0.7.0.zip, r-oldrel: SESraster_0.7.0.zip
macOS binaries: r-release (arm64): SESraster_0.7.0.tgz, r-oldrel (arm64): SESraster_0.7.0.tgz, r-release (x86_64): SESraster_0.7.0.tgz, r-oldrel (x86_64): SESraster_0.7.0.tgz
Old sources: SESraster archive

Reverse dependencies:

Reverse imports: divraster, phyloraster

Linking:

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