SDMmodelCV-class

SDMmodelCV

This Class represents a SDMmodel model object with replicates and hosts all
the models trained during the cross validation.

User-friendly framework that enables the training and the
evaluation of species distribution models (SDMs). The package implements
functions for data driven variable selection and model tuning and includes
numerous utilities to display the results. All the functions used to select
variables or to tune model hyperparameters have an interactive real-time
chart displayed in the 'RStudio' viewer pane during their execution. At the
moment only the maximum entropy method is available using the 'Java'
implementation, Phillips et al. (2006) <doi:10.1016/j.ecolmodel.2005.03.026>,
through the 'dismo' package and the 'R' implementation through the 'maxnet'
package, Phillips et al. (2017) <doi:10.1111/ecog.03049>. 'SDMtune' uses its
own script to predict maxent models, resulting in much faster predictions
for large datasets compared to native predictions from the use of the 'Java'
software. This reduces considerably the computation time when tuning the
model using the AICc.

Sergio Vignali

SDMtune

Species Distribution Model Selection

Arnaud Barras

Veronika Braunisch

Conservation Biology - University of Bern 

SDMmodelCV-class function

<dl class="dl-horizontal">
<dt><code>models</code></dt><dd>list. A list containing all the models trained during the cross
validation.</dd></dl><dt><code>p</code></dt><dd><a rd-options="" href="/link/SWD?package=SDMtune&version=0.1.0" data-mini-rdoc="SDMtune::SWD">SWD</a> object. Full dataset used by the k-fold cross validation.</dd><dt><code>a</code></dt><dd><a rd-options="" href="/link/SWD?package=SDMtune&version=0.1.0" data-mini-rdoc="SDMtune::SWD">SWD</a> object. The absence/background locations used to train the
model.</dd><dt><code>folds</code></dt><dd>numeric. Vector with the index for the k-fold partition.</dd>

SDMmodelCV-class: SDMmodelCV

Description

Arguments

Slots