threshold: Find a threshold

Description

Find a threshold (cut-off) to transform model predictions (probabilities, distances, or similar values) to a binary score (presence or absence).

Usage

# S4 method for ModelEvaluation
threshold(x, stat='', sensitivity=0.9, ...)

Value

data.frame with the following columns:

kappa: the threshold at which kappa is highest ("max kappa")

spec_sens: the threshold at which the sum of the sensitivity (true positive rate) and specificity (true negative rate) is highest

no_omission: the highest threshold at which there is no omission

prevalence: modeled prevalence is closest to observed prevalence

equal_sens_spec: equal sensitivity and specificity

sensitivty: fixed (specified) sensitivity

Arguments

x: A ModelEvaluation object (see evaluate
stat: character. To select a particular threshold (see section 'value' for possible values)
sensitivity: numeric between 0 and 1. For the fixed sensitivity threshold
...: Additional arguments. None implemented

Author

Robert J. Hijmans and Diego Nieto-Lugilde

Examples

Run this code

## See ?maxent for an example with real data.
# this is a contrived example:
# p has the predicted values for 50 known cases (locations)
# with presence of the phenomenon (species)
p <- rnorm(50, mean=0.7, sd=0.3)
# b has the predicted values for 50 background locations (or absence)
a <- rnorm(50, mean=0.4, sd=0.4)
e <- evaluate(p=p, a=a)

threshold(e)