Species Distribution Model Selection

User-friendly framework that enables the training and the evaluation of species distribution models (SDMs). The package implements functions for data driven variable selection and model tuning and includes numerous utilities to display the results. All the functions used to select variables or to tune model hyperparameters have an interactive real-time chart displayed in the 'RStudio' viewer pane during their execution. At the moment only the maximum entropy method is available using the 'Java' implementation, Phillips et al. (2006) , through the 'dismo' package and the 'R' implementation through the 'maxnet' package, Phillips et al. (2017) . 'SDMtune' uses its own script to predict maxent models, resulting in much faster predictions for large datasets compared to native predictions from the use of the 'Java' software. This reduces considerably the computation time when tuning the model using the AICc.


Reference manual

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0.1.1 by Sergio Vignali, 3 days ago


Report a bug at https://github.com/ConsBiol-unibern/SDMtune/issues

Browse source code at https://github.com/cran/SDMtune

Authors: Sergio Vignali [aut, cre] , Arnaud Barras [aut] , Veronika Braunisch [aut] , Conservation Biology - University of Bern [fnd]

Documentation:   PDF Manual  

GPL-3 license

Imports cli, crayon, dismo, ggplot2, htmltools, jsonlite, kableExtra, maxnet, methods, progress, raster, rasterVis, Rcpp, reshape2, rstudioapi, scales, stringr, whisker

Suggests covr, knitr, maps, pkgdown, rmarkdown, roxygen2, snow, testthat, zeallot

Linking to Rcpp

See at CRAN