| abies | A data set containing localities and environmental condition... |
| backg | A data set containing environmental conditions of background... |
| calib_area | Delimit calibration area for constructing species... |
| correct_colinvar | Collinearity reduction of predictor variables |
| data_bpdp | Calculate data to construct partial dependence surface plots |
| data_pdp | Calculate data to construct partial dependence plots |
| env_outliers | Integration of outliers detection methods in environmental... |
| esm_gam | Fit and validate Generalized Additive Models based on... |
| esm_gau | Fit and validate Gaussian Process models based on Ensembles... |
| esm_gbm | Fit and validate Generalized Boosted Regression models based... |
| esm_glm | Fit and validate Generalized Linear Models based on Ensembles... |
| esm_max | Fit and validate Maximum Entropy Models based on Ensemble of... |
| esm_net | Fit and validate Neural Networks based on Ensembles of Small... |
| esm_svm | Fit and validate Support Vector Machine models based on... |
| extra_eval | Measure model extrapolation based on Shape extrapolation... |
| extra_truncate | Truncate suitability predictions based on an extrapolation... |
| fit_ensemble | Ensemble model fitting and validation |
| fit_gam | Fit and validate Generalized Additive Models |
| fit_gau | Fit and validate Gaussian Process models |
| fit_gbm | Fit and validate Generalized Boosted Regression models |
| fit_glm | Fit and validate Generalized Linear Models |
| fit_max | Fit and validate Maximum Entropy models |
| fit_net | Fit and validate Neural Networks models |
| fit_raf | Fit and validate Random Forests models |
| fit_svm | Fit and validate Support Vector Machine models |
| get_block | Transform a spatial partition layer to the same spatial... |
| hespero | A data set containing localities of Hesperocyparis... |
| homogenize_na | Homogenize cells with NAs across all layers |
| interp | Raster interpolation between two time periods |
| msdm_posteriori | Methods to correct overprediction of species distribution... |
| msdm_priori | Create spatial predictor variables to reduce overprediction... |
| occfilt_env | Perform environmental filtering on species occurrences |
| occfilt_geo | Perform geographical filtering on species occurrences |
| occfilt_select | Select filtered occurrences |
| part_random | Conventional data partitioning methods |
| part_sband | Spatial band cross-validation |
| part_sblock | Spatial block cross-validation |
| part_senv | Environmental and spatial cross-validation |
| p_bpdp | Bivariate partial dependence plot |
| p_extra | Graphical exploration of extrapolation or suitability pattern... |
| plot_res | Plot different resolutions to be used in part_sblock |
| p_pdp | Partial Dependent Plot |
| sample_background | Sample background points |
| sample_pseudoabs | Sample pseudo-absences |
| sdm_directory | Create directories for saving the outputs of the flexsdm |
| sdm_eval | Calculate different model performance metrics |
| sdm_extract | Extract environmental data values from a spatial raster based... |
| sdm_predict | Spatial predictions from individual and ensemble models |
| sdm_summarize | Merge model performance tables |
| sdm_varimp | Calculate permutation-based variable importance scores for... |
| spp | A data set containing presences and absences of three virtual... |
| tune_gbm | Fit and validate Generalized Boosted Regression models with... |
| tune_max | Fit and validate Maximum Entropy models with exploration of... |
| tune_net | Fit and validate Neural Networks models with exploration of... |
| tune_raf | Fit and validate Random Forest models with exploration of... |
| tune_svm | Fit and validate Support Vector Machine models with... |
