Package index • isdmtools

Folds Creation & Management

Core functions for spatial partitioning.

create_folds() bind_datasets(): Create block cross-validation folds for multisource spatial datasets
extract_fold() plot(<DataFolds>) print(<DataFolds>) summary(<DataFolds>) autoplot(<DataFolds>): Methods for manipulating data from DataFolds object.

Evaluate the balance and quality of spatial folds.

check_folds(): Check Spatial Folds Independence
check_env_balance(): Check Environmental Balance of Folds
summarise_fold_diagnostics() print(<FoldsSummary>): Summarise Fold Diagnostics
print(<GeoDiagnostic>) plot(<GeoDiagnostic>): Methods for GeoDiagnostic objects
print(<EnvDiagnostic>) plot(<EnvDiagnostic>): Methods for EnvDiagnostic objects

Background sampling and model performance evaluation.

compute_metrics(): Compute Evaluation Metrics for Integrated Spatial Models from Multisource Datasets
sample_background(): Generate background points
plot(<BackgroundPoints>) print(<BackgroundPoints>): Methods for BackgroundPoints objects
as.data.frame(<ISDMmetrics>) print(<ISDMmetrics>) summary(<ISDMmetrics>) plot(<ISDMmetrics>) `[`(<ISDMmetrics>) get_background(): Methods for ISDMmetrics Objects

Habitat suitability analysis & mapping

suitability_index(): Compute a unified suitability index from integrated spatial model predictions.
format_predictions(): Obtain a formatted output from spatial predictions.
generate_maps(): Generate Multi-panel Maps from Spatial Model Predictions
simulate_replicates(): Replicate response data from the posterior predictive distribution.
compute_ppc_stats(): Compute Posterior Predictive Check (PPC) Statistics
print(<ppc_stats>) plot(<ppc_stats>): Posterior Predictive Check (PPC) Statistics

Data cleaning and numerical calculation

calc_niche_overlap(): Calculate Niche Overlap (Schoener's D)
fill_na_near(): Fill NA cells with the nearest cells values
solve_practical_range(): Solve the practical range of a Matérn covariance function
std_matern_corr(): Standardise Matern covariance parameters and compute the pairwise correlation from LGCP models
plot(<std_matern_corr>): Plot standardized pairwise correlation or covariance for Matern family