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SDMSelect: A R-package for cross-validation model selection and species distribution mapping

Authors: Sébastien Rochette;

SDMSelect: A R-package for cross-validation model selection and species distribution mapping

Abstract

A R-package for cross-validation model selection and species distribution mapping Added pkgdown page on github Allow for factors in presence-absence models (transformed as 0/1) Correct options with version 0.1.0 of {GlobalOptions} fixed NaN could be returned when comparing distribution with itself in best_distri. Reduce number of outputs saved at each iteration to only the best ones. With a lot of covariates tested, saving all model tested was too huge. Too keep more models, modelselect_opt$lim_pvalue can be lowered. Save outputs of model selection as rds, not RData. Added gplot_data, a modified version of rasterVis::gplot to retrieve data of raster for visualisation instead of directly plotting it in ggplot.

Keywords

species distribution model, model comparison, glm, gam

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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