| as_dgtf_sim | Coerce a list of simulated data to a 'dgtf_sim' object |
| covid_scz_2020 | Daily new COVID-19 cases, Santa Cruz County, California |
| dgtf | Fit a DGTF model |
| dgtf-err | System error distribution components |
| dgtf-gain | Gain function components |
| dgtf-lag | Lag distribution components |
| dgtf-link | Link-function components |
| dgtf-obs | Observation distribution components |
| dgtf-priors | Prior distribution constructors |
| dgtf-seasonality | Seasonality constructors |
| dgtf-sys | System-equation components |
| dgtf_compare | Side-by-side comparison of fitted DGTF models, PPC objects, or forecasts |
| dgtf_compare_params | Per-parameter posterior summaries across multiple fits |
| dgtf_compare_plot | Compare fitted DGTF model plots |
| dgtf_distributed_lag | Distributed lag model |
| dgtf_forecast_fit | Out-of-sample forecasts from a DGTF fit |
| dgtf_hawkes | Discretized Hawkes model |
| dgtf_koyck | Koyck distributed lag model |
| dgtf_model | Build a DGTF model |
| dgtf_nb_ar | Negative binomial AR model with time-varying coefficients |
| dgtf_poisson_ar | Poisson AR model with time-varying coefficients |
| dgtf_prior | Aggregate priors for inference |
| dgtf_simulate_model | Simulate from a DGTF model |
| dist_beta | Prior distribution constructors |
| dist_gamma | Prior distribution constructors |
| epiestim_baseline | EpiEstim R_t baseline for model comparison |
| err_constant | System error distribution components |
| err_gaussian | System error distribution components |
| ess | Effective sample size of an MCMC chain |
| extract_state_draws | Latent state posterior draws |
| fitted.dgtf_fit | Fitted values, residuals and predictions of a fitted DGTF model |
| gain_exponential | Gain function components |
| gain_identity | Gain function components |
| gain_logistic | Gain function components |
| gain_ramp | Gain function components |
| gain_softplus | Gain function components |
| half_cauchy | Prior distribution constructors |
| half_normal | Prior distribution constructors |
| half_t | Prior distribution constructors |
| inv_gamma | Prior distribution constructors |
| lag_lognormal | Lag distribution components |
| lag_nbinom | Lag distribution components |
| lag_uniform | Lag distribution components |
| link_exponential | Link-function components |
| link_identity | Link-function components |
| link_logistic | Link-function components |
| mcmc_control | MCMC control |
| normal | Prior distribution constructors |
| obs_nbinom | Observation distribution components |
| obs_nbinom_p | Observation distribution components |
| obs_normal | Observation distribution components |
| obs_poisson | Observation distribution components |
| param_recovery | Posterior recovery of static parameters against truth |
| plot.dgtf_forecast | Plot a posterior predictive forecast |
| plot.dgtf_sim | Plot a simulated DGTF series |
| plot_dgtf_lag | Lag distribution comparison plot |
| plot_dgtf_y | In-sample fit and out-of-sample forecast on one plot |
| plot_dgtf_y_compare | Multi-method in-sample + forecast comparison plot |
| posterior_predict | Posterior predictive draws |
| posterior_predict.dgtf_fit | Posterior predictive draws |
| predict.dgtf_fit | Fitted values, residuals and predictions of a fitted DGTF model |
| print.summary.dgtf_fit | Summarize a fitted DGTF model |
| residuals.dgtf_fit | Fitted values, residuals and predictions of a fitted DGTF model |
| rhat | Split-Rhat (Gelman-Rubin) convergence diagnostic |
| seas_none | Seasonality constructors |
| seas_period | Seasonality constructors |
| seas_weekly | Seasonality constructors |
| sim_hawkes | Default simulated count series with ground-truth model and latents |
| summary.dgtf_fit | Summarize a fitted DGTF model |
| sys_identity | System-equation components |
| sys_nbinom | System-equation components |
| sys_shift | System-equation components |
| uniform | Prior distribution constructors |
| vb_control | Hybrid variational approximation control |