Man pages for spatialRF
Easy Spatial Modeling with Random Forest

aucArea under the ROC curve
auto_corMulticollinearity reduction via Pearson correlation
auto_vifMulticollinearity reduction via Variance Inflation Factor
beowulf_clusterCreate a Beowulf cluster for parallel computing
case_weightsGenerate case weights for imbalanced binary data
default_distance_thresholdsDefault distance thresholds for spatial predictors
dot-vif_to_dfConvert VIF values to data frame
double_center_distance_matrixDouble-center a distance matrix
filter_spatial_predictorsRemove redundant spatial predictors
get_evaluationExtract evaluation metrics from cross-validated model
get_importanceExtract variable importance from model
get_importance_localExtract local variable importance from model
get_moranExtract Moran's I test results for model residuals
get_performanceExtract out-of-bag performance metrics from model
get_predictionsExtract fitted predictions from model
get_residualsExtract model residuals
get_response_curvesExtract response curve data for plotting
get_spatial_predictorsExtract spatial predictors from spatial model
is_binaryCheck if variable is binary with values 0 and 1
make_spatial_foldCreate spatially independent training and testing folds
make_spatial_foldsCreate multiple spatially independent training and testing...
memCompute Moran's Eigenvector Maps from distance matrix
mem_multithresholdCompute Moran's Eigenvector Maps across multiple distance...
moranMoran's I test for spatial autocorrelation
moran_multithresholdMoran's I test across multiple distance thresholds
normalityNormality test of a numeric vector
objects_sizeDisplay sizes of objects in current R environment
optimization_functionCompute optimization scores for spatial predictor selection
pcaCompute Principal Component Analysis
pca_multithresholdCompute Principal Component Analysis at multiple distance...
pipePipe operator
plants_dfPlant richness and predictors for American ecoregions
plants_distanceDistance matrix between ecoregion edges
plants_predictorsPredictor variable names for plant richness examples
plants_responseResponse variable name for plant richness examples
plants_rfExample fitted random forest model
plants_rf_spatialExample fitted spatial random forest model
plants_xyCoordinates for plant richness data
plot_evaluationVisualize spatial cross-validation results
plot_importanceVisualize variable importance scores
plot_moranPlots a Moran's I test of model residuals
plot_optimizationOptimization plot of a selection of spatial predictors
plot_residuals_diagnosticsPlot residuals diagnostics
plot_response_curvesPlots the response curves of a model.
plot_response_surfacePlots the response surfaces of a random forest model
plot_training_dfScatterplots of a training data frame
plot_training_df_moranMoran's I plots of a training data frame
plot_tuningPlots a tuning object produced by 'rf_tuning()'
prepare_importance_spatialPrepares variable importance objects for spatial models
printCustom print method for random forest models
print_evaluationPrints cross-validation results
print_importancePrints variable importance
print_moranPrints results of a Moran's I test
print_performanceprint_performance
rank_spatial_predictorsRanks spatial predictors
rescale_vectorRescales a numeric vector into a new range
residuals_diagnosticsNormality test of a numeric vector
rfRandom forest models with Moran's I test of the residuals
rf_compareCompares models via spatial cross-validation
rf_evaluateEvaluates random forest models with spatial cross-validation
rf_importanceContribution of each predictor to model transferability
rf_repeatFits several random forest models on the same data
rf_spatialFits spatial random forest models
rf_tuningTuning of random forest hyperparameters via spatial...
root_mean_squared_errorRMSE and normalized RMSE
select_spatial_predictors_recursiveFinds optimal combinations of spatial predictors
select_spatial_predictors_sequentialSequential introduction of spatial predictors into a model
setup_parallel_executionSetup parallel execution with automatic backend detection
standard_errorStandard error of the mean of a numeric vector
statistical_modeStatistical mode of a vector
the_feature_engineerSuggest variable interactions and composite features for...
thinningApplies thinning to pairs of coordinates
thinning_til_nApplies thinning to pairs of coordinates until reaching a...
weights_from_distance_matrixTransforms a distance matrix into a matrix of weights
spatialRF documentation built on Dec. 20, 2025, 1:07 a.m.