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