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, ) implemented for raster data.

SESraster

Randomization of presence/absence species distribution raster data 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.

Installation

To install the package, run:

install.packages("SESraster")

The development version can be installed from the Github repository:

require(devtools)
install_github("HemingNM/SESraster", build_vignettes = TRUE)

SESraster basics

Basic information about the package can be found below, at the package's webpage, or in the vignettes browseVignettes("SESraster")

Null model algorithms

vignette("null-models"): For an overview of the null model algorithms for species co-occurrence analysis summarized in (Gotelli 2000, doi:10.2307/177478).

Spatial null model algorithms in SESraster

vignette("spatial-null-models"): Get started with SESraster. See installation instructions and how the implemented null model algorithms work with spatial data.

Standardized effect sizes

vignette("SES"): For computing standardized effect sizes (SES) using the implemented null model algorithms.

Citation

If you use this R package, please cite in your publications:

Heming N. M., Mota F. M. M., Alves-Ferreira G. (2023). SESraster: Raster Randomization for Null Hypothesis Testing. R package version 0.7.0, https://CRAN.R-project.org/package=SESraster