hemingnm / sesraster

Randomization of presence/absence species distribution raster data for calculating standardized effect sizes and testing null hypothesis.

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

• For more information:

citation("SESraster")

Issues

If you have any question or find any bug, let us know through the topic "Issues".