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SDMtune (version 0.2.0)

Species Distribution Model Selection

Description

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.

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Version

Install

install.packages('SDMtune')

Monthly Downloads

437

Version

0.2.0

License

GPL-3

Maintainer

Sergio Vignali

Last Published

September 2nd, 2019

Functions in SDMtune (0.2.0)

Print Correlated Variables

Maxent Variable Importance

Merge SWD Objects

Plot Prediction

Artificial Neural Network

Confusion Matrix

Boosted Regression Tree

Sample With Data

old2NewSDMmodelCV

Convert Old SDMmodelCV object

MaxEnt Thresholds

Convert Old SWD object

Reduce Variables

old2NewSDMmodel

Convert Old SDMmodel object

get_tunable_args

Get Tunable Arguments

Get Dataset Subsample, Deprecated

Plot Response Curve

plot,SDMtune,missing-method

Plot SDMtune object

Plot Correlation

Virtual Species

Variable Selection

Convert Old SDMtune object

predict,ANN-method

predict,BRT-method

Train, Validation and Test datasets

predict,Maxent-method

predict,RF-method

predict,SDMmodel-method

Prepare an SWD object

Plot Variable Importance

Plot Presence Absence Map

Plot Jackknife Test

Create Random Folds

Variable Importance

True Skill Statistics

SDMmodel2MaxEnt

SDMmodel2MaxEnt

SDMtune: A package for tuning Species Distribution Models.

SDMmodelCV-class