maxentVarImp: Maxent Variable Importance

In SDMtune: Species Distribution Model Selection

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.

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.

Value

A data frame with the variable importance.

Author(s)

Sergio Vignali

See Also

maxentTh.

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 Maxent model
# The next line checks if Maxent is correctly configured but you don't need
# to run it in your script
model <- train(method = "Maxent",
               data = data,
               fc = "l")

maxentVarImp(model)

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