Fitted model with maxnet algorithm

A maxnet fitted_models object resulting from fit_selected() using calibration data with based on WorldCLim variables.

Usage

data("fitted_model_maxnet")

Format

A fitted_models with the following elements:

species

Species names

Models

A list with the fitted maxnet models (replicates and full models)

calibration_data

A data.frame containing the variables extracted for presence and background points

continuous_variables

A character indicating the names of the continuous variables

categorical_variables

A character indicating the names of the categorical variables

selected_models

A data.frame with formulas and evaluation metrics for each selected model

weights

A numeric vector specifying weights for the occurrence records. NULL if no weights were set.

pca

A prcomp object containing PCA results. NULL if PCA was not performed.

addsamplestobackground

A logical value indicating whether to add any presence point not already included to the background.

omission_rate

A numeric value indicating the omission rate used to evaluate models.

thresholds

A numeric vector with thresholds used to binarize each replicate and the consensus (mean and median), calculated based on the omission rate defined in calibration().

algorithm

A character string indicating the algorithm used (maxnet).

partition_method

A character string indicating the partitioning method used.

n_replicates

A numeric value indicating the number of replicates or folds.

train_proportion

A numeric value indicating the proportion of occurrences used for training when the partition method is 'subsample' or 'bootstrap'.