independent_eval1 {enmpa}

Evaluate final models using independent data

Description

Final evaluation steps for model predictions using an independent dataset (not used in model calibration).

Usage

independent_eval1(prediction, threshold, test_prediction = NULL,
                  lon_lat = NULL)

independent_eval01(prediction, observation, lon_lat = NULL)

Arguments

prediction

(numeric) vector or SpatRaster object. If numeric, predicted values in independent data (for independent_eval01), or the entire area of prediction (for independent_eval1). If SpatRaster prediction over the area of interest.

threshold

(numeric) the lowest predicted probability value for an occurrence point. This value must be defined for presences-only data. Default = NULL.

test_prediction

(numeric) vector of predictions for independent data. Default = NULL.

lon_lat

matrix or data.frame of coordinates (longitude and latitude, in that order) of independent data. Points must be located within the valid area of prediction. For independent_eval01 they must correspond with values in observation.

observation

(numeric) vector of observed (known) values of presence or absence to test against prediction (if numeric) or values of prediction in lon_lat.

Value

A data.frame or list containing evaluation results.

Examples

# Independent test data based on coordinates (lon/lat WGS 84) from presence
# and absences records
data("test", package = "enmpa")
head(test)

# Loading a model prediction
pred <- terra::rast(system.file("extdata", "proj_out_wmean.tif",
                                package = "enmpa"))
terra::plot(pred)

# Evaluation using presence-absence data
independent_eval01(prediction = pred, observation = test$Sp,
                   lon_lat = test[, 2:3])

# Evaluation using presence-only data
test_p_only <- test[test$Sp == 1, ]
th_maxTSS   <- 0.1274123            # threshold based on the maxTSS

independent_eval1(prediction = pred, threshold = th_maxTSS,
                  lon_lat = test_p_only[, 2:3])