Class to store results of model cross-validation with presence/absence (0/1) data
Slots
presence:
presence data used
absence:
absence data used
np:
number of presence points
na:
number of absence points
auc:
Area under the receiver operator (ROC) curve
pauc:
p-value for the AUC (for the Wilcoxon test W statistic
cor:
Correlation coefficient
pcor:
p-value for correlation coefficient
t:
vector of thresholds used to compute confusion matrices
confusion:
confusion matrices
prevalence:
Prevalence
ODP:
Overall diagnostic power
CCR:
Correct classification rate
TPR:
True positive rate
TNR:
True negative rate
FPR:
False positive rate
FNR:
False negative rate
PPP:
Positive predictive power
NPP:
Negative predictive power
MCR:
Misclassification rate
OR:
Odds-ratio
kappa:
Cohen's kappa
Author(s)
Robert J. Hijmans
References
Fielding, A. H. & J.F. Bell, 1997. A review of methods for the assessment of prediction errors in conservation presence/absence models. Environmental Conservation 24: 38-49
Liu, C., M. White & G. Newell, 2011. Measuring and comparing the accuracy of species distribution models with presence-absence data. Ecography 34: 232-243.