Function reference • SBC

Datasets Generating datasets ready for use with SBC and working with them.
`bind_datasets()`	Combine multiple datasets together.
`generate_datasets()`	Generate datasets.
`SBC_datasets()`	Create new `SBC_datasets` object.
`[`(<SBC_datasets>)	Subset an `SBC_datasets` object.
`SBC_generator_brms()`	Create a brms generator.
`SBC_generator_custom()`	Wrap a function the creates a complete dataset.
`SBC_generator_function()`	Generate datasets via a function that creates a single dataset.
`calculate_prior_sd()`	Calculate prior standard deviation of a dataset
Backends Represent various inference engines you can use with SBC.
`SBC_backend_brms()`	Build a backend based on the `brms` package.
`SBC_backend_brms_from_generator()`	Build a brms backend, reusing the compiled model from a previously created `SBC_generator_brms` object.
`SBC_backend_cmdstan_sample()`	Backend based on sampling via `cmdstanr`.
`SBC_backend_cmdstan_variational()`	Backend based on variational approximation via `cmdstanr`.
`SBC_backend_default_thin_ranks()`	S3 generic to get backend-specific default thinning for rank computation.
`SBC_backend_hash_for_cache()`	Get hash used to identify cached results.
`SBC_backend_iid_draws()`	S3 generic to let backends signal that they produced independent draws.
`SBC_backend_mock()`	A mock backend.
`SBC_backend_rstan_optimizing()`	SBC backend using the `optimizing` method from `rstan`.
`SBC_backend_rstan_sample()`	SBC backend using the `sampling` method from `rstan`.
`SBC_fit()`	Use backend to fit a model to data.
`SBC_fit_to_diagnostics()`	S3 generic to get backend-specific diagnostics.
Computation & results Functions related to running the SBC computation and handling the results.
`compute_SBC()`	Fit datasets and evaluate diagnostics and SBC metrics.
`generated_quantities()`	Create a definition of generated quantities evaluated in R.
`statistics_from_single_fit()`	Recompute SBC statistics given a single fit.
`recompute_SBC_statistics()`	Recompute SBC statistics without refitting models.
`bind_results()`	Combine multiple SBC results together.
`check_all_SBC_diagnostics()`	Check diagnostics and issue warnings when those fail.
`plot_coverage()`	Plot the observed coverage and its uncertainty
`SBC_example_results()`	Combine an example backend with an example generator to provide full results that can be used to test other functions in the package.
`SBC_results()`	SBC_results objects.
`[`(<SBC_results>)	Subset the results.
`calculate_ranks_draws_matrix()`	Calculate ranks given variable values within a posterior distribution.
`get_diagnostic_messages()`	Get diagnostic messages for `SBC_results` or other objects.
`SBC_fit_to_diagnostics()`	S3 generic to get backend-specific diagnostics.
`default_chunk_size()`	Determines the default chunk size.
`default_cores_per_fit()`	Determines the default cores per single fit.
Plotting & Summarising Plotting and summarising results
`data_for_ecdf_plots()`	Maybe not export in the end? Useful for debugging
`plot_ecdf()` `plot_ecdf_diff()`	Plot the ECDF-based plots.
`plot_contraction()`	Prior/posterior contraction plot.
`plot_coverage()`	Plot the observed coverage and its uncertainty
`plot_rank_hist()`	Plot rank histogram of an SBC results.
`plot_sim_estimated()`	Plot the simulated "true" values versus posterior estimates
`guess_rank_hist_bins()`	Guess the number of bins for `plot_rank_hist()`.
`empirical_coverage()`	Compute observed coverage of posterior credible intervals.
Miscellaneous
`wasserstein()`	wasserstein distance between binned samples
`cjs_dist()`	Cumulative Jensen-Shannon divergence
`combine_args()`	Combine two named lists and overwrite elements with the same name using the value from args2
`max_diff()`	Max difference between binned samples with the same length
`rank2unif()`	Distance between binned draws (rank for SBC) and discrete uniform
`set2set()`	Summarize relational property of overall prior and posterior draws

Reference

Datasets

Backends

Computation & results

Plotting & Summarising

Miscellaneous