Calculate AUC, TSS, and RMSE for given density predictions and validation data
Usage
evaluation_metrics(x, x.idx, y, y.idx, count.flag = FALSE)
Value
A numeric vector with AUC, TSS and RMSE values, respectively.
If count.flag == FALSE, the RMSE value will be NA
Arguments
x
object of class sf; SDM predictions
x.idx
name or index of column in x with prediction values
y
object of class sf; validation data
y.idx
name or index of column in y with validation data.
This validation data column must have at least two unique values, e.g. 0 and 1
count.flag
logical; TRUE indicates that the data in column y.idx is count data,
while FALSE indicates that the data is presence/absence.
See details for differences in data processing based on this flag.
Details
If count.flag == TRUE, then eSDM::model_abundance(x, x.idx, FALSE) will be run
to calculate predicted abundance and thus calculate RMSE.
Note that this assumes the data in column x.idx of x are density values.
If count.flag == FALSE, then all of the values in column y.idx of y must be 0 or 1.
All rows of x with a value of NA in column x.idx and
all rows of y with a value of NA in column y.idx are removed before calculating metrics