env.evaluate: Calculates evaluation metrics (AUC, etc.) using latin...

In ENMTools: Analysis of Niche Evolution using Niche and Distribution Models

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)

ENMTools documentation built on April 11, 2023, 6:09 p.m.