evaluation_metrics {eSDM} | R Documentation |
Calculate SDM evaluation metrics
Description
Calculate AUC, TSS, and RMSE for given density predictions and validation data
Usage
evaluation_metrics(x, x.idx, y, y.idx, count.flag = FALSE)
Arguments
x |
object of class sf; SDM predictions |
x.idx |
name or index of column in |
y |
object of class sf; validation data |
y.idx |
name or index of column in |
count.flag |
logical; |
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
Value
A numeric vector with AUC, TSS and RMSE values, respectively.
If count.flag == FALSE
, the RMSE value will be NA
Examples
evaluation_metrics(preds.1, 2, validation.data, "sight")
evaluation_metrics(preds.1, "Density2", validation.data, "count", TRUE)