Functions to calculate fuzzy versions of species' occurrence patterns based on presence-absence data (including inverse distance interpolation, trend surface analysis and prevalence-independent favourability GLM), and pair-wise fuzzy similarity (based on fuzzy versions of commonly used similarity indices) among those occurrence patterns. Includes also functions for model comparison (overlap and fuzzy similarity, loss or gain), and for data preparation, such as obtaining unique abbreviations of species names, converting species lists (long format) to presence-absence tables (wide format), transposing part of a data frame, assessing the false discovery rate, or analysing and dealing with multicollinearity among variables. Includes also sample datasets for providing practical examples.
TO DO:
pairwiseRangemaps (calculate area of pairwise intersection and union between rangemaps)
rangemapSim (calculate rangemap similarity using common similarity indices)
fuzzyOverlay: modifications reflecting function changes
modOverlap: example now provided
fuzzyOverlay, fuzzyRangeChange, modOverlap:
fuzzyOverlay (calculate row-wise intersection, union, expansion, contraction or consensus among continuous model predictions)
fuzzyRangeChange (calculate overal loss, gain, and maintenance of favourability between models)
corSelect (select among correlated variables based on their bivariate relationship with the response)
modOverlap (asses the total overlap between model predictions using niche comparison metrics)