Given an object returned by
specificity and proportion correctly classified (
pcc) validation statistics - calculated using either the
seegSDM functions. Note that
auc is calculated with a
seegSDM clone of the auc function in
PresenceAbsence but in which worse-than-random AUC scores are not inverted.
cv = TRUE the estimates returned are the means of the validation statistics and their standard deviations calculated against the witheld data for each of the
n.folds folds in the BRT run. That is, if the arguments
n.folds = 10, bag.fraction = 0.75 are passed to
runBRT, the resulting BRT model will be an average of 10 separate BRT models, each of them train on a subset of 75% of the data. The validation statistics for each fold are calculated by comparing the predictions of each fold model against the 25% of the data which was witheld for that fold. Estimated standard deviations for these statistics are also calculated (by the functions in the
PresenceAbsence package). The mean of these statistics across the 10 folds is what is reported.
cv = TRUE and
pwd = TRUE, these cv statistics are calculated using the pairwise distance sampling procedure (
pwdSample) of Hijmans (2012) to ensure that accuracy statistics are not inflated by increasing the pseudo-absence selection distance in presence-only models
cv = FALSE the statistics are calculated once on the full training set using the final full model.
pwd = TRUE cannot be used in this case.
A list of BRT model bootstraps, each element being an output from runBRT.
Whether to calculate cross-validation statistics using folds (
Whether to use the pairwise distance sampling procedure (
The threshold distance for the pairwise distance sampling procedure, passed directly to the argument
Other arguments to pass to
A vector giving the mean cross-validation statistics and mean standard deviations for these across the folds (see decription for details).
Hijmans, R.J., 2012. Cross-validation of species distribution models: removing spatial sorting bias and calibration with a null-model. Ecology 93: 679-688
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