Package index • SDMtune

Prepare Data

Function to prepare data for SDMsel analysis

addSamplesToBg(): Add Samples to Background

prepareSWD(): Prepare an SWD object

randomFolds(): Create Random Folds

thinData(): Thin Data

trainValTest(): Train, Validation and Test datasets

Modeling

Function to train the model and get information from the model

getTunableArgs(): Get Tunable Arguments

modelReport(): Model Report

maxentTh(): MaxEnt Thresholds

maxentVarImp(): Maxent Variable Importance

predict(<ANN>): Predict ANN

predict(<BRT>): Predict BRT

predict(<Maxent>): Predict Maxent

predict(<Maxnet>): Predict Maxnet

predict(<RF>): Predict RF

predict(<SDMmodel>): Predict

predict(<SDMmodelCV>): Predict for Cross Validation

train(): Train

thresholds(): Thresholds

varImp(): Variable Importance

Evaluating

Function to evaluate the model

aicc(): AICc

auc(): AUC

confMatrix(): Confusion Matrix

doJk(): Jackknife Test

tss(): True Skill Statistics

Data-driven Variable selection

Function to perform Data-driven Variable selection

corVar(): Print Correlated Variables

reduceVar(): Reduce Variables

varSel(): Variable Selection

Plot

Function to plot results

plotCor(): Plot Correlation

plotJk(): Plot Jackknife Test

show(<SDMtune>) plot(<SDMtune>,<missing>): SDMtune class

plotPA(): Plot Presence Absence Map

plotPred(): Plot Prediction

plotResponse(): Plot Response Curve

plotROC(): Plot ROC curve

plotVarImp(): Plot Variable Importance

Tune

Function for model tuning and optimization

gridSearch(): Grid Search

optimizeModel(): Optimize Model

randomSearch(): Random Search

Utilities

Some utility functions

checkMaxentInstallation(): Check Maxent Installation

combineCV(): Combine Cross Validation models

mergeSWD(): Merge SWD Objects

SDMmodel2MaxEnt(): SDMmodel2MaxEnt

swd2csv(): SWD to csv

Dataset

Dataset provided with the package

virtualSp: Virtual Species

Classes

Package classes

show(<ANN>): Artificial Neural Network

show(<BRT>): Boosted Regression Tree

show(<Maxent>): Maxent

show(<Maxnet>): Maxnet

show(<RF>): Random Forest

show(<SDMmodel>): SDMmodel

show(<SDMmodelCV>): SDMmodelCV

show(<SDMtune>) plot(<SDMtune>,<missing>): SDMtune class

show(<SWD>): Sample With Data