env.evaluate {ENMTools}

Calculates evaluation metrics (AUC, etc.) using latin hypercube sampling in environment space

Description

Calculates evaluation metrics (AUC, etc.) using latin hypercube sampling in environment space

Usage

env.evaluate(
  species,
  model,
  env,
  bg.source = "background",
  n.background = 10000,
  test.eval = FALSE,
  verbose = FALSE,
  ...
)

Arguments

species

An enmtools.species object

model

An enmtools.model object or a model that can be projected using the predict() function of dismo

env

A SpatRaster of environmental data.

bg.source

Determines whether minima and maxima of the environment space should be picked using the environment layers or the background points.

n.background

The number of background points to sample from the environment space.

test.eval

When set to "true", env.evaluate evaluates the test data stored in the model object instead of the training data.

verbose

Controls printing of various messages progress reports. Defaults to FALSE.

...

Arguments to be passed to othfer functions

Value

A dismo evaluate object measuring the performance of model predictions in environment space.

Examples

cyreni <- iberolacerta.clade$species$cyreni
cyreni.glm <- enmtools.glm(cyreni, euro.worldclim, test.prop = 0.2,
f = pres ~ bio1 + bio12, nback = 500)
env.evaluate(cyreni, cyreni.glm,  euro.worldclim)