plotROC: Plots the Receiver Operating Charactersitic (ROC) Curve
In cghaase/GARPTools: Tools for GARP Data Prep and Model Evaluation

Description Usage Arguments Details Value See Also Examples

plotROC Plots the ROC curve of the best model subset output from GARP, relating 1-model specificity to model sensitivity

1	plotROC(n, x, points)

`n`	a numeric value specifying the number of models in the best subset output from GARP
`x`	a raster object of the summated raster of the best models output from GARP
`points`	a spatial object of presence data to use for testing locations

For discrete cutpoints (n), represents the number of models that agree on a predicted presence location.

The raster object (x) should be a raster representing the number of models that agree on a predicted presence location per pixel and that outtput by sumRasters.

The shapefile points should presence locations that were not used by GARP for model training and those output by splitData.

A plot of the ROC curve.

aucGARP

  set.seed(0)
  library(raster)
  r   <- raster(ncols = 100, nrows = 100)
  r[] <- rbinom(5, 10, 0.3)
  hs  <- data.frame("Latitude" = c(-89, 72, 63, 42, 54), "Longitude" = c(-12, 13, 24, 26, 87), "Species" = rep("Homo_sapiens", 5))
  plotROC(n = 10, x = r, points = SpatialPoints(hs[,1:2]))