Package: SESraster 0.7.0

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.

Authors:Neander Marcel Heming [aut, cre, cph], Flávio M. M. Mota [aut], Gabriela Alves-Ferreira [aut]

SESraster_0.7.0.tar.gz
SESraster_0.7.0.zip(r-4.5)SESraster_0.7.0.zip(r-4.4)SESraster_0.7.0.zip(r-4.3)
SESraster_0.7.0.tgz(r-4.4-any)SESraster_0.7.0.tgz(r-4.3-any)
SESraster_0.7.0.tar.gz(r-4.5-noble)SESraster_0.7.0.tar.gz(r-4.4-noble)
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SESraster.pdf |SESraster.html
SESraster/json (API)
NEWS

# Install 'SESraster' in R:
install.packages('SESraster', repos = c('https://hemingnm.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/hemingnm/sesraster/issues

On CRAN:

null-modelsrandomizationrasterspatialspatial-analysisspecies-distribution-modelling

6.51 score 6 stars 2 packages 30 scripts 208 downloads 9 exports 3 dependencies

Last updated 1 years agofrom:9e26b7c420. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 01 2024
R-4.5-winOKOct 01 2024
R-4.5-linuxOKOct 01 2024
R-4.4-winOKOct 01 2024
R-4.4-macOKOct 01 2024
R-4.3-winOKOct 01 2024
R-4.3-macOKOct 01 2024

Exports:algorithm_metricsbootspat_ffbootspat_naivebootspat_strfit.memoryfr2probload_ext_dataplot_alg_metricsSESraster

Dependencies:Rcpprlangterra

Null model algorithms

Rendered fromnull-models.Rmdusingknitr::rmarkdownon Oct 01 2024.

Last update: 2023-07-21
Started: 2023-07-17

Spatial null model algorithms in SESraster

Rendered fromspatial-null-models.Rmdusingknitr::rmarkdownon Oct 01 2024.

Last update: 2023-07-20
Started: 2023-07-17

Standardized effect sizes

Rendered fromSES.Rmdusingknitr::rmarkdownon Oct 01 2024.

Last update: 2023-07-17
Started: 2023-07-17