Package index • ddsynth

Data Synthesis

Functions for synthesising delay distribution data

create_data_map(): Create a global map of dataset geographic distribution
create_scenario(): Create a scenario with specific characteristics
generate_cdf_plot_simulation_study_input(): Plot true CDFs for simulation study input scenarios
generate_data_table(): Generate a multi-page landscape LaTeX data summary table
generate_hierarchical_data_mixed(): Generate data from hierarchical model with mixed summary types and sample sizes
generate_matched_moments_plot(): Matched-moments distribution comparison plot
generate_results_table(): Generate a LaTeX summary table of incubation period estimates
generate_results_table_split(): Generate a LaTeX summary table split into three panels by data availability
generate_scenario_library(): Generate a comprehensive set of scenarios
prepare_stan_data_from_datasets(): Prepare Stan data from a list of dataset summaries
extract_dataset_summary(): Extract a tidy summary of all built-in datasets
filter_datasets(): Filter a dataset list by subgroup and/or location

Functions for fitting hierarchical Bayesian models

fit_model(): Fit Stan model to simulated data
run_simulation_study_generalized(): Run simulation study with generalized scenarios
bsl_bridge_estimate(): Compute a log-mean-exp bridge estimate of the marginal likelihood
bsl_create_model(): Create a BSL model object
bsl_get_summary_stats(): Compute predictive summary statistics from BSL posterior draws
bsl_make_density_summary(): Compute posterior predictive density summary for plotting
bsl_make_posterior_summary(): Compute posterior predictive density or CDF summary for plotting
bsl_make_trace_df(): Build a tidy trace data frame from a multi-chain BSL fit list
bsl_run_diagnostics(): Run automated MCMC diagnostics on BSL fits and save plots/CSV
bsl_summarise_posteriors(): Summarise BSL posteriors with point estimates and 95% credible intervals
bsl_to_mcmc_list_multi(): Convert a multi-chain BSL fit list to coda mcmc.list objects
make_stan_init_fn(): Create a Stan initialisation function from prior means
pre_inference_checks(): Run pre-inference checks on a list of datasets
should_attempt_gg(): Check whether the Generalised Gamma is likely identifiable from a dataset
update_phi_prior(): Update the log_phi prior mean from method-of-moments estimates

Functions for summarising and visualising results

compute_pathogen_model_bayes_factors(): Compute LOO-based model weights for all pathogens
plot_main_figure(): Build the main incubation-period analysis figure
plot_main_figure_split(): Split main figure into three panels by data availability

Functions for evaluating simulation study performance

check_coverage(): Compute coverage for a parameter
compute_iqd(): Compute Integrated Quadratic Distance (IQD)
compute_median_bias(): Compute median bias
compute_predictive_cdf(): Compute posterior predictive CDF from a fitted Stan model
compute_posterior_predictive_quantile_ci(): Compute credible interval for posterior predictive quantiles
compute_true_marginal_quantile(): Compute true marginal quantiles of the predictive distribution
compute_wis(): Compute the mean Weighted Interval Score for the posterior predictive distribution
extract_quantiles(): Extract quantiles from a predictive CDF summary
gamma_type2_reliable(): Check whether Gamma can be reliably fitted from median + IQR summary statistics
summarise_parameters(): Summarise posterior parameter estimates across BSL models

ddsynth ddsynth-package: ddsynth: Delay Distribution from Summary Statistics