Function reference • SBC

Datasets Generating datasets ready for use with SBC and working with them.
`SBC_datasets()`	Create new `SBC_datasets` object.
`bind_datasets()`	Combine multiple datasets together.
`generate_datasets()`	Generate datasets.
`[`(<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
`attribute_present()`	Get attribute presence for a vector of variable names.
`attribute_present_stats()`	Check an attribute in the `$stats` element of the results for presence of an attribute.
`combine_var_attributes()`	Combine multiple sets of variable attributes.
`remove_attribute_from_stats()`	Remove an attribute from a `data.frame` column with attributes.
`var_attributes()` `validate_var_attributes()` `possibly_constant_var_attribute()` `binary_var_attribute()` `hidden_var_attribute()` `na_valid_var_attribute()` `inf_valid_var_attribute()` `submodel_var_attribute()`	Predefined constants to use for variable attributes recognized by SBC.
Backends Represent various inference engines you can use with SBC.
`SBC_backend_bridgesampling()`	Backend using bridgesampling to do Bayes factor calculation (and Bayesian Model Averaging) over two candidate models.
`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_cached()`	A backend that wraps another backend with a caching scheme.
`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_extractBF_comparison()`	A backend for Bayes factor workflow with BayesFactor::extractBF.
`SBC_backend_function()`	A backend that just calls a function.
`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_lmBF()`	A backend using `BayesFactor::lmBF()`
`SBC_backend_mock()`	A mock backend.
`SBC_backend_postprocess_cached_fit()` `SBC_backend_preprocess_fit_for_cache()`	Allows the backend to do any pre-/post- processing on a fit stored to / loaded from cache.
`SBC_backend_rjags()`	Create a JAGS backend using `rjags`
`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()`	S3 generic using backend to fit a model to data.
`SBC_fit_to_BFBayesFactor()`	A fits need to implement this S3 generic to be useful for the `SBC_backend_extractBF_comparison()` backend.
`SBC_fit_to_bridge_sampler()`	Convert a fit for a given backend into a bridge sampler object.
`SBC_fit_to_diagnostics()`	S3 generic to get backend-specific diagnostics.
`SBC_fit_to_draws_matrix()`	S3 generic converting a fitted model to a `draws_matrix` object.
`SBC_posterior_cdf()`	Use a fitted model to obtain a posterior CDF at a given point.
Computation & results Functions related to running the SBC computation and handling the results.
`compute_SBC()`	Fit datasets and evaluate diagnostics and SBC metrics.
`SBC_results()`	Create an `SBC_results` object
`binary_calibration_from_bp()` `plot_binary_calibration_diff()` `plot_binary_calibration()`	Binary prediction calibration computation and visualisation.
`check_all_SBC_diagnostics()`	Check diagnostics and issue warnings when those fail.
`split_SBC_results_for_bf()`	Split stats from SBC of Bayes factor into stats for the individual submodels.
`[`(<SBC_results>)	Subset the results.
`bind_derived_quantities()`	Combine two lists of derived quantities
`derived_quantities()`	Create a definition of derived quantities evaluated in R.
`validate_derived_quantities()`	Validate a definition of derived quantities evaluated in R.
`compute_dquants()`	Compute derived quantities based on given data and posterior draws.
`bind_globals()`	Combine two sets globals for use in derived quantities or backend
`SBC_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.
`calculate_ranks_draws_matrix()`	Calculate ranks given variable values within a posterior distribution.
`SBC_fit_to_diagnostics()`	S3 generic to get backend-specific diagnostics.
`get_diagnostic_messages()`	Get diagnostic messages for `SBC_results` or other objects.
`default_chunk_size()`	Determines the default chunk size.
`default_cores_per_fit()`	Determines the default cores per single fit.
`binary_probabilities_from_stats()`	Extract binary probabilities from SBC stats.
`cached_fit_filename()`	Provide a file where a cached result of a fit will be/was stored.
`get_stats_for_submodel()`	Extract stats for a submodel from a Bayes factor results
Plotting & Summarising Plotting and summarising results
`plot_ecdf()` `plot_ecdf_diff()`	Plot the ECDF-based plots.
`binary_calibration_from_bp()` `plot_binary_calibration_diff()` `plot_binary_calibration()`	Binary prediction calibration computation and visualisation.
`data_for_ecdf_plots()`	Maybe not export in the end? Useful for debugging
`plot_contraction()`	Prior/posterior contraction plot.
`plot_coverage()` `plot_coverage_diff()`	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.
`combine_all_variables()` `combine_array_elements()`	Helper functions to be passed to ECDF-plots to combine variables in a single panel.
`combine_args()`	Combine two named lists and overwrite elements with the same name using the value from args2
`combine_var_attributes()`	Combine multiple sets of variable attributes.
`gaffke_ci()` `gaffke_p()` `gaffke_test()`	Non-parametric test for the mean of a bounded variable.
`brier_resampling_test()` `brier_resampling_p()` `binary_miscalibration()` `miscalibration_resampling_p()` `miscalibration_resampling_test()`	Binary calibration tests
Examples Functions to let you easily test the pacakge
`SBC_example_backend()`	Construct a backend to be used in the examples.
`SBC_example_generator()`	Construct a generator used in the examples.
`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_print_example_model()`	Print the Stan code of a model used in the examples.
Miscellaneous
`combine_args()`	Combine two named lists and overwrite elements with the same name using the value from args2

Reference

Datasets

Backends

Computation & results

Plotting & Summarising

Examples

Miscellaneous