Plot Variable Importance

Plot the variable importance as a bar plot.

Usage

plotVarImp(df, color = "grey")

Arguments

df

data.frame. A data.frame containing the the name of the variables as first column and the value of the variable importance as second column.

color

character. The colour of the bar plot.

Value

A ggplot object.

Author

Sergio Vignali

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")
#> ℹ Extracting predictor information for presence locations
#> ✔ Extracting predictor information for presence locations [39ms]
#> 
#> ℹ Extracting predictor information for absence/background locations
#> ✔ Extracting predictor information for absence/background locations [68ms]
#> 

# 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")