# 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 model
model <- train(method = "Maxnet", data = data, fc = "l")
# Compute variable importance
vi <- varImp(model, permut = 1)
# Plot variable importance
plotVarImp(vi)
# Plot variable importance with custom color
plotVarImp(vi, color = "red")
# }
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