View source: R/6.f.threshold.R
thrshld | R Documentation |
This function will apply the selected threshold criterias to MaxEnt model projection(s) of a 'mcmp' object and save on the folder "3_out.MaxEnt/Mdls.[species name]/Mdls.thrshld". For each projection (species and climatic scenario), two layers will be generated, one with suitability above the threshold value and another with presence/absence only.
thrshld(mcmp, thrshld.i = 4:6, t.all = FALSE, sp.nm = "species", numCores = 1)
mcmp |
An object returned by |
thrshld.i |
List of threshold criteria to be applied. Use numbers to choose the desired one(s). Current options: 1. Fixed.cumulative.value.1 (fcv1); 2. Fixed.cumulative.value.5 (fcv5); 3. Fixed.cumulative.value.10 (fcv10); 4. Minimum.training.presence (mtp); 5. 10.percentile.training.presence (x10ptp); 6. Equal.training.sensitivity.and.specificity (etss); 7. Maximum.training.sensitivity.plus.specificity (mtss); 8. Balance.training.omission.predicted.area.and.threshold.value (bto); 9. Equate.entropy.of.thresholded.and.original.distributions (eetd). |
t.all |
logical. Should threshold be applied on individual and consensus projections? Default is FALSE. Ignored if consensus projections are not found. |
sp.nm |
Species name. Used to name the output folder |
numCores |
Number of cores to use for parallelization. If set to 1, no paralellization is performed |
Stack or brick of thresholded predictions
thrshld_b
## Not run:
mods.thrshld <- thrshld(mcmp=mxnt.mdls.preds, thrshld.i = 4:6)
plot(mods.thrshld[[1]][[2]]) # continuous
plot(mods.thrshld[[2]][[2]]) # binary
## End(Not run)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.