aicc: AICc

In SDMtune: Species Distribution Model Selection

AICc

Description

Compute the Akaike Information Criterion corrected for small samples size (Warren and Seifert, 2011).

Usage

aicc(model, env)

Arguments

model	SDMmodel object.
env	rast containing the environmental variables.

Details

The function is available only for Maxent and Maxnet methods.

Value

The computed AICc

Author(s)

Sergio Vignali

References

Warren D.L., Seifert S.N., (2011). Ecological niche modeling in Maxent: the importance of model complexity and the performance of model selection criteria. Ecological Applications, 21(2), 335–342.

See Also

auc and tss.

Examples

# Acquire environmental variables
files <- list.files(path = file.path(system.file(package = "dismo"), "ex"),
                    pattern = "grd",
                   full.names = TRUE)

predictors <- terra::rast(files)

# Prepare presence and background locations
p_coords <- virtualSp$presence
bg_coords <- virtualSp$background

# Create SWD object
data <- prepareSWD(species = "Virtual species",
                   p = p_coords,
                   a = bg_coords,
                   env = predictors,
                   categorical = "biome")

# Train a model
model <- train(method = "Maxnet",
               data = data,
               fc = "l")

# Compute the AICc
aicc(model,
     env = predictors)

SDMtune documentation built on July 9, 2023, 6:03 p.m.