| dynamic_prior | Specify priors for a dynamic count / binomial model |
| fit_dynamic_model | Fit a Bayesian dynamic count / binomial time-series model |
| forecast | Generic forecast function |
| forecast.dynamic_fit | Forecast a fitted dynamic model |
| med_weekly | Weekly Mediterranean crossings (Mediterranean example) |
| plot.dynamic_fit | Plot method for fitted dynamic models |
| plot_fitted | Plot observed versus fitted values |
| plot_forecast | Plot observed history, fitted values and forecast with uncertainty |
| plot_latent | Plot the fitted latent trajectory |
| plot_zero_inflation | Plot zero-inflation diagnostics |
| predict.dynamic_fit | In-sample fitted values and posterior predictive replicates |
| simulate_dynamic_binomial | Simulate a binomial dynamic series |
| simulate_dynamic_poisson | Simulate a Poisson dynamic series |
| structural_zero_prob | Posterior probability that each observed zero is structural |
| summary.dynamic_fit | Summarise a fitted dynamic model |
| uk_weekly | Weekly English Channel crossings (UK example) |