Learn R Programming

PresenceAbsence (version 1.1.11)

Presence-Absence Model Evaluation

Description

Provides a set of functions useful when evaluating the results of presence-absence models. Package includes functions for calculating threshold dependent measures such as confusion matrices, pcc, sensitivity, specificity, and Kappa, and produces plots of each measure as the threshold is varied. It will calculate optimal threshold choice according to a choice of optimization criteria. It also includes functions to plot the threshold independent ROC curves along with the associated AUC (area under the curve).

Copy Link

Version

Install

install.packages('PresenceAbsence')

Monthly Downloads

3,197

Version

1.1.11

License

Unlimited

Last Published

January 7th, 2023

Functions in PresenceAbsence (1.1.11)

calibration.plot

Calibration Plot
pcc

Percent Correctly Classified
presence.absence.summary

Presence/Absence Summary Plots
roc.plot.calculate

ROC Plot Calculations
optimal.thresholds

Calculate Optimal Thresholds
sensitivity

Sensitivity
specificity

Specificity
presence.absence.simulation

Presence/Absence Data Simulation
presence.absence.hist

Presence/Absence Histogram
predicted.prevalence

Predicted Prevalence
presence.absence.accuracy

Accuracy Table for Presence/Absence Data
SPPREV

Overall Preavalences for Species Presence/Absence Data
SPDATA

Species Presence/Absence Data
SIM3DATA

Simulated Presence-Absence Data
PresenceAbsence-package

Presence-Absence model evaluation
error.threshold.plot

Error Threshold Plot
cmx

Confusion Matrix
Kappa

Kappa
auc

Area Under the Curve
auc.roc.plot

AUC ROC Plot