auc                     Area under the ROC curve
auto_cor                Multicollinearity reduction via Pearson
                        correlation
auto_vif                Multicollinearity reduction via Variance
                        Inflation Factor
beowulf_cluster         Defines a beowulf cluster
case_weights            Generates case weights for binary data
default_distance_thresholds
                        Default distance thresholds to generate spatial
                        predictors
distance_matrix         Matrix of distances among ecoregion edges.
double_center_distance_matrix
                        Double centers a distance matrix
filter_spatial_predictors
                        Removes redundant spatial predictors
get_evaluation          Gets performance data frame from a
                        cross-validated model
get_importance          Gets the global importance data frame from a
                        model
get_importance_local    Gets the local importance data frame from a
                        model
get_moran               Gets Moran's I test of model residuals
get_performance         Gets out-of-bag performance scores from a model
get_predictions         Gets model predictions
get_residuals           Gets model residuals
get_response_curves     Gets data to allow custom plotting of response
                        curves
get_spatial_predictors
                        Gets the spatial predictors of a spatial model
is_binary               Checks if dependent variable is binary with
                        values 1 and 0
make_spatial_fold       Makes one training and one testing spatial
                        folds
make_spatial_folds      Makes training and testing spatial folds
mem                     Moran's Eigenvector Maps of a distance matrix
mem_multithreshold      Moran's Eigenvector Maps for different distance
                        thresholds
moran                   Moran's I test
moran_multithreshold    Moran's I test on a numeric vector for
                        different neighborhoods
objects_size            Shows size of objects in the R environment
optimization_function   Optimization equation to select spatial
                        predictors
pca                     Principal Components Analysis
pca_multithreshold      PCA of a distance matrix over distance
                        thresholds
plant_richness_df       Plant richness and predictors of American
                        ecoregions
plot_evaluation         Plots the results of a spatial cross-validation
plot_importance         Plots the variable importance of a model
plot_moran              Plots a Moran's I test of model residuals
plot_optimization       Optimization plot of a selection of spatial
                        predictors
plot_residuals_diagnostics
                        Plot residuals diagnostics
plot_response_curves    Plots the response curves of a model.
plot_response_surface   Plots the response surfaces of a random forest
                        model
plot_training_df        Scatterplots of a training data frame
plot_training_df_moran
                        Moran's I plots of a training data frame
plot_tuning             Plots a tuning object produced by 'rf_tuning()'
prepare_importance_spatial
                        Prepares variable importance objects for
                        spatial models
print.rf                Custom print method for random forest models
print_evaluation        Prints cross-validation results
print_importance        Prints variable importance
print_moran             Prints results of a Moran's I test
print_performance       print_performance
rank_spatial_predictors
                        Ranks spatial predictors
rescale_vector          Rescales a numeric vector into a new range
residuals_diagnostics   Normality test of a numeric vector
residuals_test          Normality test of a numeric vector
rf                      Random forest models with Moran's I test of the
                        residuals
rf_compare              Compares models via spatial cross-validation
rf_evaluate             Evaluates random forest models with spatial
                        cross-validation
rf_importance           Contribution of each predictor to model
                        transferability
rf_repeat               Fits several random forest models on the same
                        data
rf_spatial              Fits spatial random forest models
rf_tuning               Tuning of random forest hyperparameters via
                        spatial cross-validation
root_mean_squared_error
                        RMSE and normalized RMSE
select_spatial_predictors_recursive
                        Finds optimal combinations of spatial
                        predictors
select_spatial_predictors_sequential
                        Sequential introduction of spatial predictors
                        into a model
standard_error          Standard error of the mean of a numeric vector
statistical_mode        Statistical mode of a vector
the_feature_engineer    Suggest variable interactions and composite
                        features for random forest models
thinning                Applies thinning to pairs of coordinates
thinning_til_n          Applies thinning to pairs of coordinates until
                        reaching a given n
vif                     Variance Inflation Factor of a data frame
weights_from_distance_matrix
                        Transforms a distance matrix into a matrix of
                        weights
