Function reference • EpiNow2

Perform End-to-End Analyses Functions that faciliate end-to-end analysis including imputing cases by infection, estimating Rt and reporting results.
`epinow()`	Real-time Rt Estimation, Forecasting and Reporting
`regional_epinow()`	Real-time Rt Estimation, Forecasting and Reporting by Region
Define, Fit and Parameterise Distributions Functions to define, fit and parameterise distributions
`bootstrapped_dist_fit()`	Fit a Subsampled Bootstrap to Integer Values and Summarise Distribution Parameters
`dist_fit()`	Fit an Integer Adjusted Exponential, Gamma or Lognormal distributions
`dist_skel()`	Distribution Skeleton
`gamma_dist_def()`	Generate a Gamma Distribution Definition Based on Parameter Estimates
`get_dist()`	Get a Literature Distribution
`lognorm_dist_def()`	Generate a Log Normal Distribution Definition Based on Parameter Estimates
`sample_approx_dist()`	Approximate Sampling a Distribution using Counts
Estimate Parameters Function to estimate time-varying parameters of interest.
`estimate_infections()`	Estimate Infections, the Time-Varying Reproduction Number and the Rate of Growth
`plot_estimates()`	Plot Estimates
`forecast_infections()`	Forecast Infections and the Time-Varying Reproduction Number
`growth_to_R()`	Convert Growth Rates to Reproduction numbers.
`R_to_growth()`	Convert Reproduction Numbers to Growth Rates
Adjust Case Counts Adjust case counts from date of infection to report
`adjust_infection_to_report()`	Adjust from Case Counts by Infection Date to Date of Report
Summarise results Summarise results
`regional_summary()`	Generate Regional Summary Output
`summarise_key_measures()`	Summarise rt and cases
`summarise_results()`	Summarise Real-time Results
Report results Functions to report results
`adjust_infection_to_report()`	Adjust from Case Counts by Infection Date to Date of Report
`create_clean_reported_cases()`	Create Clean Reported Cases
`report_cases()`	Report case counts by date of report
`report_plots()`	Report plots
`report_summary()`	Provide Summary Statistics for Estimated Infections and Rt
Plot results Plot generated results
`plot_estimates()`	Plot Estimates
`plot_summary()`	Plot a Summary of the Latest Results
`report_plots()`	Report plots
Simulate Functions to help with simulating data to evaluate the approach
`simulate_cases()`	Simulate Cases by Date of Infection, Onset and Report
Data Package datasets that may be used to parameterise other functions
`R_to_growth()`	Convert Reproduction Numbers to Growth Rates
`adjust_infection_to_report()`	Adjust from Case Counts by Infection Date to Date of Report
`allocate_delays()`	Allocate Delays into Required Stan Format
`bootstrapped_dist_fit()`	Fit a Subsampled Bootstrap to Integer Values and Summarise Distribution Parameters
`clean_nowcasts()`	Clean Nowcasts for a Supplied Date
`clean_regions()`	Clean Regions
`country_map()`	Generate a country map for a single variable.
`create_clean_reported_cases()`	Create Clean Reported Cases
`create_initial_conditions()`	Create Initial Conditions Generating Function
`create_shifted_cases()`	Create a Data Frame of Mean Delay Shifted Cases
`create_stan_args()`	Create a List of Stan Arguments
`create_stan_data()`	Create Stan Data Required for estimate_infections
`dist_fit()`	Fit an Integer Adjusted Exponential, Gamma or Lognormal distributions
`dist_skel()`	Distribution Skeleton
`epinow()`	Real-time Rt Estimation, Forecasting and Reporting
`estimate_infections()`	Estimate Infections, the Time-Varying Reproduction Number and the Rate of Growth
`example_confirmed`	Example Confirmed Case Data Set
`extract_parameter()`	Extract Samples for a Parameter from a Stan model
`extract_parameter_samples()`	Extract Parameter Samples from a Stan Model
`extract_static_parameter()`	Extract Samples from a Parameter with a Single Dimension
`fit_model_with_nuts()`	Fit a Stan Model using the NUTs sampler
`fit_model_with_vb()`	Fit a Stan Model using Varitional Inference
`forecast_infections()`	Forecast Infections and the Time-Varying Reproduction Number
`format_fit()`	Format Posterior Samples
`gamma_dist_def()`	Generate a Gamma Distribution Definition Based on Parameter Estimates
`generation_times`	Literature Estimates of Generation Times
`get_dist()`	Get a Literature Distribution
`get_generation_time()`	Get a Literature Distribution for the Generation Time
`get_incubation_period()`	Get a Literature Distribution for the Incubation Period
`get_raw_result()`	Get a Single Raw Result
`get_regional_results()`	Get Combined Regional Results
`get_regions()`	Get Folders with Nowcast Results
`global_map()`	Generate a global map for a single variable.
`growth_to_R()`	Convert Growth Rates to Reproduction numbers.
`incubation_periods`	Literature Estimates of Incubation Periods
`lognorm_dist_def()`	Generate a Log Normal Distribution Definition Based on Parameter Estimates
`make_conf()`	Format Credible Intervals
`map_prob_change()`	Categorise the Probability of Change for Rt
`plot_estimates()`	Plot Estimates
`plot_summary()`	Plot a Summary of the Latest Results
`process_region()`	Process regional estimate
`process_regions()`	Process all Region Estimates
`regional_epinow()`	Real-time Rt Estimation, Forecasting and Reporting by Region
`regional_summary()`	Generate Regional Summary Output
`report_cases()`	Report case counts by date of report
`report_plots()`	Report plots
`report_summary()`	Provide Summary Statistics for Estimated Infections and Rt
`run_region()`	Run epinow with Regional Processing Code
`sample_approx_dist()`	Approximate Sampling a Distribution using Counts
`setup_future()`	Set up Future Backend
`setup_logging()`	Setup Logging
`simulate_cases()`	Simulate Cases by Date of Infection, Onset and Report
`stop_timeout()`	Timeout Error
`summarise_key_measures()`	Summarise rt and cases
`summarise_results()`	Summarise Real-time Results
`theme_map()`	Custom Map Theme
Map results Optional mapping functions (requires additional dependencies)
`country_map()`	Generate a country map for a single variable.
`global_map()`	Generate a global map for a single variable.
`map_prob_change()`	Categorise the Probability of Change for Rt
`theme_map()`	Custom Map Theme
Utilities Utility functions
`create_clean_reported_cases()`	Create Clean Reported Cases
`create_initial_conditions()`	Create Initial Conditions Generating Function
`create_shifted_cases()`	Create a Data Frame of Mean Delay Shifted Cases
`create_stan_args()`	Create a List of Stan Arguments
`create_stan_data()`	Create Stan Data Required for estimate_infections
`allocate_delays()`	Allocate Delays into Required Stan Format
`fit_model_with_nuts()`	Fit a Stan Model using the NUTs sampler
`fit_model_with_vb()`	Fit a Stan Model using Varitional Inference
`extract_parameter()`	Extract Samples for a Parameter from a Stan model
`extract_parameter_samples()`	Extract Parameter Samples from a Stan Model
`extract_static_parameter()`	Extract Samples from a Parameter with a Single Dimension
`format_fit()`	Format Posterior Samples
`clean_regions()`	Clean Regions
`run_region()`	Run epinow with Regional Processing Code
`process_region()`	Process regional estimate
`process_regions()`	Process all Region Estimates
`get_regions()`	Get Folders with Nowcast Results
`get_raw_result()`	Get a Single Raw Result
`get_regional_results()`	Get Combined Regional Results
`get_dist()`	Get a Literature Distribution
`get_generation_time()`	Get a Literature Distribution for the Generation Time
`get_incubation_period()`	Get a Literature Distribution for the Incubation Period
`clean_nowcasts()`	Clean Nowcasts for a Supplied Date
`make_conf()`	Format Credible Intervals
`map_prob_change()`	Categorise the Probability of Change for Rt
`setup_logging()`	Setup Logging
`setup_future()`	Set up Future Backend

Reference

Perform End-to-End Analyses

Define, Fit and Parameterise Distributions

Estimate Parameters

Adjust Case Counts

Summarise results

Report results

Plot results

Simulate

Data

Map results

Utilities