Calculates spatially corrected, threshold-dependent metrics for
an observational data set and model predictions (Kappa and confusion matrix)
Usage
th.dep(data, coord, thresh = 0.5, spatial = TRUE)
Arguments
data
A data frame or matrix with two columns. The first column
should contain actual presence/absence data (binary, 0 or 1) and the
second column should contain model predictions of probability of
occurrence (numeric, between 0 and 1).
coord
A data frame or matrix with two columns containing x,y
coordinates for each actual and predicted value. Coordinates must be
integer and consecutively numbered.
thresh
A cutoff value for classifying predictions as modeled
presences or modeled absences. Default is 0.5.
spatial
A logical indicating whether spatially corrected indices
(rather than classical indices) should be computed.
Value
A list with the following components:
kappa
Kappa statistic
cm
Confusion matrix
sensitivity
Sensitivity
specificity
Specificity
actuals
Actual occurrence data or adjusted actual occurrence data
splitlevel.pred
Level splitting of predicted values
splitlevel.act
Level splitting of actuals or adjusted actuals
splitposition.pred
Position splitting of predicted values
splitposition.act
Position splitting of actuals or adjusted actuals
References
Carl G, Kuehn I (2017) Spind: a package for computing
spatially corrected accuracy measures.
Ecography 40: 675-682. DOI: 10.1111/ecog.02593