plotJk: Plot Jackknife Test

In SDMtune: Species Distribution Model Selection

Plot Jackknife Test

Description

Plot the Jackknife Test for variable importance.

Usage

plotJk(jk, type = c("train", "test"), ref = NULL)

Arguments

jk	data.frame with the output of the doJk function.
type	character, "train" or "test" to plot the result of the test on the train or testing dataset.
ref	numeric. The value of the chosen metric for the model trained using all the variables. If provided it plots a vertical line showing the reference value.

Value

A ggplot object.

Author(s)

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")

# Split presence locations in training (80%) and testing (20%) datasets
datasets <- trainValTest(data,
                         test = 0.2,
                         only_presence = TRUE)
train <- datasets[[1]]
test <- datasets[[2]]

# Train a model
model <- train(method = "Maxnet",
               data = train,
               fc = "lq")

# Execute the Jackknife test for all the environmental variables using the
# metric AUC
jk <- doJk(model,
           metric = "auc",
           test = test)

# Plot Jackknife test result for training
plotJk(jk,
       type = "train",
       ref = auc(model))

#' # Plot Jackknife test result for testing
plotJk(jk,
       type = "test",
       ref = auc(model, test = test))

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