binomial_data           Simulated binomial epidemiological dataset
build_design            Build an epidemic-level DLNM design matrix
check_identifiability   Diagnose identifiability and numerical
                        stability of DLNM cross-basis designs
compare_exposures       Compare chronological exposure profiles
compare_periods         Compare period-specific DLNM effects
compare_predictions     Compare predicted outcomes between exposure
                        scenarios
compute_eci             Compute Exposure Cumulative Impact
compute_ecilag          Compute lag-specific decomposition of Exposure
                        Cumulative Impact (ECI)
define_exposures        Define DLNM exposure templates
define_periods          Define epidemiological lag periods
ensemble_bestfit        Create model and lag-contribution ensembles
                        from best-fit DLNM models
epi_data                Simulated beta epidemiological dataset
epi_sensitivity         Compute sensitivity of exposure-response curves
find_bestfit            Find the best DLNM model structure using
                        grouped validation
fit_epidlnm             Fit a harmonized DLNM inferential model
gamma_data              Simulated gamma epidemiological dataset
gaussian_data           Simulated gaussian epidemiological dataset
nb2_data                Simulated negative-binomial epidemiological
                        dataset
plot_eci                Plot ECI and lag-specific contribution results
plot_effects            Plot lag-specific or period-specific effects
plot_losses             Plot simulated yield and economic losses
plot_performance        Plot out-of-fold model performance
plot_scenarios          Plot predictions across epidemiological
                        scenarios
poisson_data            Simulated poisson epidemiological dataset
predict_outcomes        Predict outcomes from fitted EpiExposure DLNM
                        models
prepare_response        Prepare and validate the epidemic-level
                        response for modeling
reduce_effects          Reduce a fitted DLNM to a one-dimensional
                        association
simulate_exposures      Simulate chronological exposure profiles
simulate_losses         Simulate yield and economic losses
simulate_ranges         Generate exposure-value scenarios across DLNM
                        lag periods
simulate_scenarios      Simulate epidemiological exposure-profile
                        scenarios
spatial_replicate       Simulated epidemiological data with independent
                        spatial replicates
spatial_year            Simulated epidemiological data with independent
                        spatial fields by year
st_poisson              Simulated spatial poisson epidemiological
                        dataset
summarise_effects       Summarise DLNM exposure-lag effects on link and
                        response scales
