Generate trinary maps from species presence, background and model prediction

This function takes in the species presence and background data, along with a model, and generates trinary maps. It also calculates the information for ROC curves.

Usage

trinaryMapWorkflow(
  pres,
  background,
  rModel,
  NATo0 = TRUE,
  maxTPQuantile = 0.3,
  sdMultiplier = 2,
  max.sens = 0.95,
  smoothMethod = "binormal"
)

Arguments

pres: A data.frame object containing the species presence data
background: A data.frame object containing the background data
rModel: A spatRaster object containing the model data
NATo0: A logical indicating whether to turn NA values into zeros in the presence and background data
maxTPQuantile: A numeric value representing the quantile of the predicted values at presence locations used to determine the upper threshold for presence predictions. For example, a value of `0.3` means the function uses the 30th percentile of the predicted presence values as the upper threshold, ensuring that the model maintains at least 70 sensitivity. Default is `0.3`.
sdMultiplier: A numeric value that controls the adjustment of the lower threshold for presence predictions. It multiplies the standard deviation of the predicted values at presence locations to define this lower threshold. If this threshold results in a negative value, it is adjusted to zero by default. Default is `2`.
max.sens: value of sensitivity to use if no upper limit is found based on derivatives. default is 0.95
smoothMethod: default is 'binormal'

Value

A list containing the trinary thresholds and trinary rasters