SDMtune (version 1.1.1)

maxentVarImp: Maxent Variable Importance

Description

Shows the percent contribution and permutation importance of the environmental variables used to train the model.

Usage

maxentVarImp(model)

Arguments

model

'>SDMmodel or '>SDMmodelCV object trained using the "Maxent" method.

Value

A data frame with the variable importance.

Details

When an '>SDMmodelCV object is passed to the function, the output is the average of the variable importance of each model trained during the cross validation.

See Also

maxentTh.

Examples

# NOT RUN {
# Acquire environmental variables
files <- list.files(path = file.path(system.file(package = "dismo"), "ex"),
                    pattern = "grd", full.names = TRUE)
predictors <- raster::stack(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 Maxent model
# The next line checks if Maxent is correctly configured but you don't need
# to run it in your script
if (checkMaxentInstallation(verbose = FALSE)) {
model <- train(method = "Maxent", data = data, fc = "l")
maxentVarImp(model)
}
# }