Package index • EpiNow2

Estimation + Reporting

Functions that facilitate end-to-end analysis including imputing cases by infection, estimating Rt and reporting results.

as_forecast_sample(<estimate_infections>) as_forecast_sample(<epinow>) as_forecast_sample(<forecast_secondary>) as_forecast_sample(<estimate_truncation>) experimental: Convert EpiNow2 model output to a forecast_sample object
epinow(): Real-time Rt Estimation, Forecasting and Reporting
epinow2_cmdstan_model(): Load and compile an EpiNow2 cmdstanr model
get_parameters(): Get parameters from distributions or fitted models
get_samples(): Get posterior samples from a fitted model
print(<epinowfit>): Print information about an object that has resulted from a model fit.
regional_epinow(): Real-time Rt Estimation, Forecasting and Reporting by Region
summary(<epinow>): Summary output from epinow

Estimate, Simulate, and Forecast Parameters

Function to estimate, simulate and forecast parameters of interest.

estimate_infections(): Estimate Infections, the Time-Varying Reproduction Number and the Rate of Growth
forecast_infections(): Forecast infections from a given fit and trajectory of the time-varying reproduction number
estimate_secondary(): Estimate a Secondary Observation from a Primary Observation
forecast_secondary(): Forecast Secondary Observations Given a Fit from estimate_secondary
estimate_delay() deprecated: Estimate a Delay Distribution
estimate_dist() experimental: Estimate a delay distribution using primarycensored
estimate_truncation(): Estimate truncation of observed data

Specify Arguments

Functions used by estimate_infections

backcalc_opts(): Back Calculation Options
delay_opts(): Delay Distribution Options
filter_opts(): Filter Options for a Target Region
forecast_opts(): Forecast options
gt_opts() generation_time_opts(): Generation Time Distribution Options
gp_opts(): Approximate Gaussian Process Settings
obs_opts(): Observation Model Options
rt_opts(): Time-Varying Reproduction Number Options
secondary_opts(): Secondary Reports Options
stan_laplace_opts() experimental: Stan Laplace algorithm Options
stan_opts(): Stan Options
stan_pathfinder_opts() experimental: Stan pathfinder algorithm Options
stan_sampling_opts(): Stan Sampling Options
stan_vb_opts(): Stan Variational Bayes Options
trunc_opts(): Truncation Distribution Options
opts_list(): Forecast optiong

Preprocess Data

Functions used for preprocessing data

fill_missing(): Fill missing data in a data set to prepare it for use within the package
add_breakpoints(): Add breakpoints to certain dates in a data set.
filter_leading_zeros(): Filter leading zeros from a data set.
apply_zero_threshold(): Convert zero case counts to NA (missing) if the 7-day average is above a threshold.

Regional Analysis

Functions used for summarising across regions (designed for use with regional_epinow)

regional_summary(): Regional Summary Output
regional_runtimes(): Summarise Regional Runtimes
get_regional_results(): Get Combined Regional Results

Summarise Results

Functions for summarising results

summary(<epinow>): Summary output from epinow
summary(<estimate_dist>) experimental: Summarise results from estimate_dist
summary(<estimate_infections>): Summary output from estimate_infections
summary(<estimate_secondary>): Summarise results from estimate_secondary
summary(<estimate_truncation>): Summarise results from estimate_truncation
summary(<forecast_infections>): Summary output from forecast_infections
backcalc_opts(): Back Calculation Options
calc_CrI(): Calculate Credible Interval
calc_CrIs(): Calculate Credible Intervals
calc_summary_measures(): Calculate All Summary Measures
calc_summary_stats(): Calculate Summary Statistics
make_conf(): Format Credible Intervals
map_prob_change(): Categorise the Probability of Change for Rt

Plot Results

Plot generated results

plot(<dist_spec>): Plot PMF and CDF for a dist_spec object
plot(<estimate_infections>): Plot method for estimate_infections
plot(<estimate_secondary>): Plot method for estimate_secondary
plot(<estimate_truncation>): Plot method for estimate_truncation
plot(<forecast_infections>): Plot method for forecast_infections
plot(<forecast_secondary>): Plot method for forecast_secondary objects
plot_CrIs(): Plot EpiNow2 Credible Intervals
plot_estimates(): Plot Estimates
plot_summary(): Plot a Summary of the Latest Results
report_plots() superseded: Report plots

Report Results

Functions to report results

report_plots() superseded: Report plots
report_summary() superseded: Provide Summary Statistics for Estimated Infections and Rt

Distribution Functions

Functions to define and parameterise distributions

LogNormal() Gamma() Normal() Exp() Weibull() NonParametric() Fixed() Dirichlet(): Probability distributions
c(<dist_spec>): Combines multiple delay distributions for further processing
collapse(<dist_spec>): Collapse nonparametric distributions in a <dist_spec>
discretise(<dist_spec>) discretize(): Discretise a <dist_spec>
`==`(<dist_spec>) `!=`(<dist_spec>): Compares two delay distributions
fix_parameters(<dist_spec>): Fix the parameters of a <dist_spec>
get_parameters(): Get parameters from distributions or fitted models
is_constrained(<dist_spec>): Check if a <dist_spec> is constrained, i.e. has a finite maximum or nonzero CDF cutoff.
max(<dist_spec>): Returns the maximum of one or more delay distribution
mean(<dist_spec>): Returns the mean of one or more delay distribution
new_dist_spec(): Internal function for generating a dist_spec given parameters and a distribution.
plot(<dist_spec>): Plot PMF and CDF for a dist_spec object
`+`(<dist_spec>): Creates a delay distribution as the sum of two other delay distributions.
print(<dist_spec>): Prints the parameters of one or more delay distributions
bound_dist(): Define bounds of a <dist_spec>
get_pmf(): Get the probability mass function of a nonparametric distribution
get_distribution(): Get the distribution of a <dist_spec>

Fit Delay Distributions

Functions to fit delay 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

Simulation

Functions to help with simulating data or mapping to reported cases

simulate_infections(): Simulate infections using the renewal equation
simulate_secondary(): Simulate secondary observations from primary observations
convolve_and_scale(): Convolve and scale a time series

Data

Package datasets that may be used to parameterise other functions or in examples

example_generation_time: Example generation time
example_incubation_period: Example incubation period
example_reporting_delay: Example reporting delay
example_confirmed: Example Confirmed Case Data Set
example_truncated: Example Case Data Set with Truncation

Data Access

Functions for extracting data from objects or getting data from sources

get_distribution(): Get the distribution of a <dist_spec>
get_parameters(): Get parameters from distributions or fitted models
get_pmf(): Get the probability mass function of a nonparametric distribution
get_predictions(): Get predictions from a fitted model
get_regional_results(): Get Combined Regional Results
get_samples(): Get posterior samples from a fitted model
extract_CrIs(): Extract Credible Intervals Present
extract_inits() experimental: Generate initial conditions from a Stan fit
extract_samples(): Extract all samples from a stan fit
extract_stan_param(): Extract a parameter summary from a Stan object

Data Cleaning

Functions for cleaning data

clean_nowcasts(): Clean Nowcasts for a Supplied Date
clean_regions(): Clean Regions

Setup

Functions used for setting up functionality

setup_default_logging(): Setup Default Logging
setup_future(): Set up Future Backend
setup_logging(): Setup Logging

Utilities

Utility functions

run_region(): Run epinow with Regional Processing Code
expose_stan_fns(): Expose internal package stan functions in R
convert_to_logmean(): Convert mean and sd to log mean for a log normal distribution
convert_to_logsd(): Convert mean and sd to log standard deviation for a log normal distribution
growth_to_R() superseded: Convert Growth Rates to Reproduction numbers.
R_to_growth() superseded: Convert Reproduction Numbers to Growth Rates
update_secondary_args(): Update estimate_secondary default priors

Internal

EpiNow2 EpiNow2-package: EpiNow2: Estimate and Forecast Real-Time Infection Dynamics
add_day_of_week(): Adds a day of the week vector
add_horizon(): Add missing values for future dates
allocate_delays(): Allocate Delays into Required Stan Format
allocate_empty(): Allocate Empty Parameters to a List
apply_default_cdf_cutoff(): Apply default CDF cutoff to a <dist_spec> if it is unconstrained
build_np_est_data(): Build Stan data for estimated nonparametric delays
`$`(<epinow>) deprecated: Extract elements from epinow objects with deprecation errors
`$`(<estimate_infections>) deprecated: Extract elements from estimate_infections objects with deprecation errors
`$`(<estimate_secondary>) deprecated: Extract elements from estimate_secondary objects with deprecation errors
check_generation_time(): Validate probability distribution for using as generation time
check_reports_valid(): Validate data input
check_simulation_input(): Validate simulation input data frame
check_sparse_pmf_tail(): Check that PMF tail is not sparse
check_stan_delay(): Validate probability distribution for passing to stan
check_truncation_length(): Check and warn if truncation distribution is longer than observed time
check_truncation_obs_opts(): Check that obs_opts settings unused by estimate_truncation are at defaults
combine_tv_and_static_params(): Combine time-varying and static parameters
construct_output(): Construct Output
convert_to_natural(): Internal function for converting parameters to natural parameters.
copy_results_to_latest(): Copy Results From Dated Folder to Latest
create_backcalc_data(): Create Back Calculation Data
create_delay_inits(): Create initial conditions for delays
create_future_rt(): Construct the Required Future Rt assumption
create_gp_data(): Create Gaussian Process Data
create_infection_summary(): Create summary output from infection estimation objects
create_initial_conditions(): Create Initial Conditions Generating Function
create_obs_model(): Create Observation Model Settings
create_rt_data(): Create Time-varying Reproduction Number Data
create_sampling_log_message(): Create sampling log message
create_shifted_cases(): Create Delay Shifted Cases
create_stan_args(): Create a List of Stan Arguments
create_stan_data(): Create Stan Data Required for estimate_infections
create_stan_delays(): Create delay variables for stan
create_stan_params(): Create parameters for stan
discrete_pmf(): Discretised probability mass function
dist_id_to_name(): Get distribution name from primarycensored Stan dist_id
.extract_to_dist_spec(): Extract parameters and convert to dist_spec
.get_dist_id(): Map distribution name to primarycensored ID
.get_param_names(): Map distribution name to parameter names
.prepare_linelist_data(): Prepare linelist data for delay estimation
epinow2_rstan_model(): Load an EpiNow2 rstan model.
epinow2_stan_model(): Return a stan model object for the appropriate backend
estimates_by_report_date(): Estimate Cases by Report Date
extract_delay_params(): Extract delay distributions from a fitted model
extract_delays(): Extract samples from all delay parameters
extract_latent_state(): Extract samples for a latent state from a Stan model
extract_parameters(): Extract samples from all parameters
extract_params(): Extract parameter names
extract_scalar_params(): Extract scalar parameters from a fitted model
extract_single_dist(): Extract a single element of a composite <dist_spec>
fit_model(): Fit a model using the chosen backend.
fit_model_approximate(): Fit a Stan Model using an approximate method
fit_model_with_nuts(): Fit a Stan Model using the NUTs sampler
format_fit(): Format Posterior Samples
format_quantile_predictions(): Format quantile predictions
format_sample_predictions(): Format sample predictions
format_samples_with_dates(): Format raw Stan samples with dates and metadata
format_simulation_output(): Format Simulation Output from Stan
get_accumulate(): Get accumulation flags from data
get_element(): Extracts an element of a <dist_spec>
get_raw_result(): Get a Single Raw Result
get_regions(): Get Folders with Results
get_regions_with_most_reports(): Get Regions with Most Reported Cases
get_seeding_time(): Estimate seeding time from delays and generation time
lapply_func(): Choose a parallel or sequential apply function
lower_bounds(): Get the lower bounds of the parameters of a distribution
make_init_priors(): Build the stan-side init-prior data block from a list of priors
make_param(): Internal function to create a parameter list
match_output_arguments(): Match User Supplied Arguments with Supported Options
merge_trunc_pred_obs(): Merge truncation predictions with observations for display
natural_params(): Get the names of the natural parameters of a distribution
ndist(): Calculate the number of distributions in a <dist_spec>
nonparametric_pmf_data(): Build PMF data for the nonparametric branch of plot.dist_spec
pack_init_prior(): Pack a dist_spec into stan-side init-prior fields
pad_reported_cases(): Pads reported cases with daily initial zeros
posterior_to_normal(): Create a Normal distribution from posterior samples
prepare_truncation_obs(): Prepare truncation observations for Stan
process_region(): Process regional estimate
process_regions(): Process all Region Estimates
rdirichlet(): Draw a single sample from a Dirichlet
reconstruct_delay(): Reconstruct a dist_spec from stored stan data and posterior
reconstruct_nonparametric(): Reconstruct a nonparametric delay distribution
reconstruct_parametric(): Reconstruct a parametric delay distribution
regional_runtimes(): Summarise Regional Runtimes
save_estimate_infections(): Save Estimated Infections
save_input(): Save Observed Data
sd(<dist_spec>): Returns the standard deviation of one or more delay distribution
select_plots(): Internal helper function to select plots from those created by report_plots()
set_dt_single_thread(): Set to Single Threading
setup_dt(): Convert to Data Table
setup_target_folder(): Setup Target Folder for Saving
stable_convolve(): Numerically stable convolution function for two pmf vectors
`[[`(<epinow>) deprecated: Extract elements from epinow objects with bracket notation
`[[`(<estimate_infections>) deprecated: Extract elements from estimate_infections objects with bracket notation
`[[`(<estimate_secondary>) deprecated: Extract elements from estimate_secondary objects with bracket notation
summarise_key_measures(): Summarise rt and cases
summarise_results(): Summarise Real-time Results
update_horizon(): Updates Forecast Horizon Based on Input Data and Target