SDMtune (version 0.1.0)

plotVarImp: Plot Variable Importance

Description

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 color of the bar plot, default is grey.

Value

A ggplot object

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 locations
p_coords <- condor[, 1:2]

# Prepare background locations
bg_coords <- dismo::randomPoints(predictors, 5000)

# Create SWD object
presence <- prepareSWD(species = "Vultur gryphus", coords = p_coords,
                       env = predictors, categorical = "biome")
bg <- prepareSWD(species = "Vultur gryphus", coords = bg_coords,
                 env = predictors, categorical = "biome")

# Train a model
model <- train(method = "Maxnet", p = presence, a = bg, 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")
# }