aicc {SDMtune} | R Documentation |
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
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)
[Package SDMtune version 1.3.1 Index]