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_clusterDefines a beowulf cluster
case_weightsGenerates case weights for binary data
default_distance_thresholdsDefault distance thresholds to generate spatial predictors
distance_matrixMatrix of distances among ecoregion edges.
double_center_distance_matrixDouble centers a distance matrix
filter_spatial_predictorsRemoves redundant spatial predictors
get_evaluationGets performance data frame from a cross-validated model
get_importanceGets the global importance data frame from a model
get_importance_localGets the local importance data frame from a model
get_moranGets Moran's I test of model residuals
get_performanceGets out-of-bag performance scores from a model
get_predictionsGets model predictions
get_residualsGets model residuals
get_response_curvesGets data to allow custom plotting of response curves
get_spatial_predictorsGets the spatial predictors of a spatial model
is_binaryChecks if dependent variable is binary with values 1 and 0
make_spatial_foldMakes one training and one testing spatial folds
make_spatial_foldsMakes training and testing spatial folds
memMoran's Eigenvector Maps of a distance matrix
mem_multithresholdMoran's Eigenvector Maps for different distance thresholds
moranMoran's I test
moran_multithresholdMoran's I test on a numeric vector for different...
normalityNormality test of a numeric vector
objects_sizeShows size of objects in the R environment
optimization_functionOptimization equation to select spatial predictors
pcaPrincipal Components Analysis
pca_multithresholdPCA of a distance matrix over distance thresholds
plant_richness_dfPlant richness and predictors of American ecoregions
plot_evaluationPlots the results of a spatial cross-validation
plot_importancePlots the variable importance of a model
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
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...
vifVariance Inflation Factor of a data frame
weights_from_distance_matrixTransforms a distance matrix into a matrix of weights
spatialRF documentation built on Aug. 19, 2022, 5:23 p.m.