Man pages for SDMtune
Species Distribution Model Selection
| addSamplesToBg | Add Samples to Background |
| aicc | AICc |
| ANN-class | Artificial Neural Network |
| auc | AUC |
| BRT-class | Boosted Regression Tree |
| checkMaxentInstallation | Check Maxent Installation |
| combineCV | Combine Cross Validation models |
| confMatrix | Confusion Matrix |
| corVar | Print Correlated Variables |
| doJk | Jackknife Test |
| getTunableArgs | Get Tunable Arguments |
| gridSearch | Grid Search |
| Maxent-class | Maxent |
| maxentTh | MaxEnt Thresholds |
| maxentVarImp | Maxent Variable Importance |
| Maxnet-class | Maxnet |
| mergeSWD | Merge SWD Objects |
| modelReport | Model Report |
| optimizeModel | Optimize Model |
| plotCor | Plot Correlation |
| plotJk | Plot Jackknife Test |
| plotPA | Plot Presence Absence Map |
| plotPred | Plot Prediction |
| plotResponse | Plot Response Curve |
| plotROC | Plot ROC curve |
| plotVarImp | Plot Variable Importance |
| predict-ANN-method | Predict ANN |
| predict-BRT-method | Predict BRT |
| predict-Maxent-method | Predict Maxent |
| predict-Maxnet-method | Predict Maxnet |
| predict-RF-method | Predict RF |
| predict-SDMmodelCV-method | Predict for Cross Validation |
| predict-SDMmodel-method | Predict |
| prepareSWD | Prepare an SWD object |
| randomFolds | Create Random Folds |
| randomSearch | Random Search |
| reduceVar | Reduce Variables |
| RF-class | Random Forest |
| SDMmodel2MaxEnt | SDMmodel2MaxEnt |
| SDMmodel-class | SDMmodel |
| SDMmodelCV-class | SDMmodelCV |
| SDMtune-class | SDMtune class |
| SDMtune-package | SDMtune: Species Distribution Model Selection |
| swd2csv | SWD to csv |
| SWD-class | Sample With Data |
| thinData | Thin Data |
| thresholds | Thresholds |
| train | Train |
| trainValTest | Train, Validation and Test datasets |
| tss | True Skill Statistics |
| varImp | Variable Importance |
| varSel | Variable Selection |
| virtualSp | Virtual Species |
