tuneRegularization: Use the AdaLipo technique to search for the best value for...

In jscavetta95/maxentools: Species Distribution Modeling with Maxent

Description

Use the AdaLipo technique to search for the best value for the regularization hyperparameter.

Usage

tuneRegularization(occurrence_data, background_data, predictors,
  group_data, factor, range, num_iterations)

Arguments

occurrence_data	Dataframe of species occurrence coordinates and extracted environmental predictor data.
background_data	Dataframe of selected background coordinates and extracted environmental predictor data.
predictors	A RasterStack of RasterLayer objects representing the environmental predictors.
group_data	A named list of bin designation for occurrence points and background points.
factor	The factor hyperparameter value to use in model creation.
range	A 2 element vector containing the start and end point of the range of regularization values to search.
num_iterations	Number of models to create.

Value

A list of results from all created models.

jscavetta95/maxentools documentation built on Dec. 8, 2019, 1:26 p.m.