Package index • caretSDM

All functions

GBIF_data(): Retrieve Species data from GBIF

WorldClim_data(): Download WorldClim v.2.1 bioclimatic data

add_predictors() get_predictors(): Add predictors to sdm_area

add_scenarios() set_scenarios_names() scenarios_names() get_scenarios_data() select_scenarios(): Add scenarios to sdm_area

algorithms: Caret Algorithms

bioc: Bioclimatic Variables

buffer_sdm(): Create buffer around occurrences

correlate_sdm(): Correlation between projections

data_clean(): Presence data cleaning routine

gcms_ensembles(): Ensemble GCMs into one scenario

input_sdm() add_input_sdm(): input_sdm

is_input_sdm() is_sdm_area() is_occurrences() is_models() is_predictions(): is_class functions to check caretSDM data classes.

join_area(): Join Area

occ: Araucaria angustifolia occurrence data

occurrences_sdm() n_records() species_names() get_coords() occurrences_as_df() add_occurrences(): Occurrences Managing

parana: Paraná State

pca_predictors() pca_summary() get_pca_model(): Predictors as PCA-axes

pdp_sdm() get_pdp_sdm(): Model Response to Variables

plot_occurrences() plot_grid() plot_predictors() plot_scenarios() plot_predictions() mapview_grid() mapview_occurrences() mapview_predictors() mapview_scenarios() mapview_predictions() plot_background() plot_niche(): S3 Methods for plot and mapview

predict_sdm() get_predictions() get_ensembles() add_predictions(): Predict SDM models in new data

prediction_change_sdm(): Prediction Change Analysis

predictors() set_predictor_names() get_predictor_names() test_variables_names() set_variables_names(): Predictors Names Managing

print(<input_sdm>): Print method for input_sdm

print(<models>): Print method for models

print(<occurrences>): Print method for occurrences

print(<predictions>): Print method for predictions

pseudoabsences() n_pseudoabsences() pseudoabsence_method() pseudoabsence_data(): Obtain Pseudoabsences

rivs: Hydrologic Variables

salm: Salminus brasiliensis occurrence data

scen: Bioclimatic Variables

scen_rs: Bioclimatic Variables

sdm_area() get_sdm_area() add_sdm_area(): Create a sdm_area object

sdm_as_stars() sdm_as_raster() sdm_as_terra(): sdm_as_X functions to transform caretSDM data into other classes.

summary_sdm() summary_sdm_presence_only() validate_on_independent_data(): Calculates performance across resamples

select_predictors() select(<sdm_area>) select(<input_sdm>) mutate(<sdm_area>) mutate(<input_sdm>) filter(<sdm_area>) filter(<input_sdm>) filter(<occurrences>) filter_species(): Tidyverse methods for caretSDM objects

train_sdm() get_tune_length() algorithms_used() get_models() get_validation_metrics() mean_validation_metrics() add_models(): Train SDM models

tsne_sdm(): tSNE

tuneGrid_sdm(): Retrieve tuneGrid from models

use_esm(): Ensemble of Small Models (ESM) in caretSDM

use_mem(): MacroEcological Models (MEM) in caretSDM

varImp_sdm(): Calculation of variable importance for models

vif_predictors() vif_summary() selected_variables(): Calculate VIF

write_ensembles() write_predictions() write_predictors() write_models() write_gpkg() write_occurrences() write_pseudoabsences() write_grid() write_validation_metrics(): Write caretSDM data