Package index • EpiNow2

Estimation + Reporting

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

epinow() stable: Real-time Rt Estimation, Forecasting and Reporting

epinow2_cmdstan_model(): Load and compile an EpiNow2 cmdstanr model

plot(<epinow>) maturing: Plot method for epinow

regional_epinow() maturing: Real-time Rt Estimation, Forecasting and Reporting by Region

summary(<epinow>) stable: Summary output from epinow

Estimate, Simulate, and Forecast Parameters

Function to estimate, simulate and forecast parameters of interest.

estimate_infections() maturing: Estimate Infections, the Time-Varying Reproduction Number and the Rate of Growth

forecast_infections() stable: Forecast infections from a given fit and trajectory of the time-varying reproduction number

estimate_secondary() stable: Estimate a Secondary Observation from a Primary Observation

forecast_secondary() experimental: Forecast Secondary Observations Given a Fit from estimate_secondary

estimate_delay() maturing: Estimate a Delay Distribution

estimate_truncation() stable: Estimate Truncation of Observed Data

Specify Arguments

Functions used by estimate_infections

backcalc_opts() stable: Back Calculation Options

delay_opts() stable: Delay Distribution Options

filter_opts() maturing: Filter Options for a Target Region

forecast_opts() stable: Forecast options

gt_opts() generation_time_opts() stable: Generation Time Distribution Options

gp_opts() stable: Approximate Gaussian Process Settings

obs_opts() stable: Observation Model Options

rt_opts() stable: Time-Varying Reproduction Number Options

secondary_opts() stable: Secondary Reports Options

stan_laplace_opts() experimental: Stan Laplace algorithm Options

stan_opts() stable: Stan Options

stan_pathfinder_opts() experimental: Stan pathfinder algorithm Options

stan_sampling_opts() stable: Stan Sampling Options

stan_vb_opts() stable: Stan Variational Bayes Options

trunc_opts() stable: Truncation Distribution Options

opts_list() maturing: Forecast optiong

Preprocess Data

Functions used for preprocessing data

fill_missing() experimental: 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() maturing: Regional Summary Output

regional_runtimes() maturing: Summarise Regional Runtimes

get_regional_results() stable: Get Combined Regional Results

Summarise Results

Functions for summarising results

summary(<epinow>) stable: Summary output from epinow

summary(<estimate_infections>) stable: Summary output from estimate_infections

backcalc_opts() stable: Back Calculation Options

calc_CrI() stable: Calculate Credible Interval

calc_CrIs() stable: Calculate Credible Intervals

calc_summary_measures() stable: Calculate All Summary Measures

calc_summary_stats() stable: Calculate Summary Statistics

make_conf() stable: Format Credible Intervals

map_prob_change() stable: Categorise the Probability of Change for Rt

Plot Results

Plot generated results

plot(<dist_spec>) experimental: Plot PMF and CDF for a dist_spec object

plot(<epinow>) maturing: Plot method for epinow

plot(<estimate_infections>) maturing: Plot method for estimate_infections

plot(<estimate_secondary>) experimental: Plot method for estimate_secondary

plot(<estimate_truncation>) experimental: Plot method for estimate_truncation

plot_CrIs() stable: Plot EpiNow2 Credible Intervals

plot_estimates() questioning: Plot Estimates

plot_summary() questioning: Plot a Summary of the Latest Results

report_plots() questioning: Report plots

Report Results

Functions to report results

report_plots() questioning: Report plots

report_summary() questioning: Provide Summary Statistics for Estimated Infections and Rt

Distribution Functions

Functions to define and parameterise distributions

LogNormal() Gamma() Normal() Fixed() NonParametric(): Probability distributions

c(<dist_spec>) experimental: Combines multiple delay distributions for further processing

collapse(<dist_spec>) experimental: Collapse nonparametric distributions in a <dist_spec>

discretise(<dist_spec>) discretize() experimental: Discretise a <dist_spec>

`==`(<dist_spec>) `!=`(<dist_spec>): Compares two delay distributions

fix_parameters(<dist_spec>) experimental: Fix the parameters of a <dist_spec>

is_constrained(<dist_spec>) experimental: Check if a <dist_spec> is constrained, i.e. has a finite maximum or nonzero CDF cutoff.

max(<dist_spec>) experimental: Returns the maximum of one or more delay distribution

mean(<dist_spec>) experimental: Returns the mean of one or more delay distribution

new_dist_spec() experimental: Internal function for generating a dist_spec given parameters and a distribution.

plot(<dist_spec>) experimental: Plot PMF and CDF for a dist_spec object

`+`(<dist_spec>) experimental: Creates a delay distribution as the sum of two other delay distributions.

print(<dist_spec>) experimental: Prints the parameters of one or more delay distributions

bound_dist() experimental: Define bounds of a <dist_spec>

get_parameters() experimental: Get parameters of a parametric distribution

get_pmf() experimental: Get the probability mass function of a nonparametric distribution

get_distribution() experimental: Get the distribution of a <dist_spec>

Fit Delay Distributions

Functions to fit delay distributions

bootstrapped_dist_fit() stable: Fit a Subsampled Bootstrap to Integer Values and Summarise Distribution Parameters

dist_fit() stable: 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 stable: Example generation time

example_incubation_period stable: Example incubation period

example_reporting_delay stable: Example reporting delay

example_confirmed stable: Example Confirmed Case Data Set

example_truncated stable: Example Case Data Set with Truncation

Data Access

Functions for extracting data from objects or getting data from sources

get_distribution() experimental: Get the distribution of a <dist_spec>

get_parameters() experimental: Get parameters of a parametric distribution

get_pmf() experimental: Get the probability mass function of a nonparametric distribution

get_regional_results() stable: Get Combined Regional Results

extract_CrIs() stable: 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() stable: Extract a Parameter Summary from a Stan Object

Data Cleaning

Functions for cleaning data

clean_nowcasts() stable: Clean Nowcasts for a Supplied Date

clean_regions() stable: Clean Regions

Setup

Functions used for setting up functionality

setup_default_logging() questioning: Setup Default Logging

setup_future() stable: Set up Future Backend

setup_logging() questioning: Setup Logging

Utilities

Utility functions

run_region() maturing: Run epinow with Regional Processing Code

expose_stan_fns() stable: Expose internal package stan functions in R

convert_to_logmean() stable: Convert mean and sd to log mean for a log normal distribution

convert_to_logsd() stable: Convert mean and sd to log standard deviation for a log normal distribution

growth_to_R() questioning: Convert Growth Rates to Reproduction numbers.

R_to_growth() questioning: Convert Reproduction Numbers to Growth Rates

update_secondary_args() stable: Update estimate_secondary default priors

Internal

EpiNow2 EpiNow2-package: EpiNow2: Estimate Real-Time Case Counts and Time-Varying Epidemiological Parameters

add_day_of_week(): Adds a day of the week vector

add_horizon(): Add missing values for future dates

allocate_delays() stable: Allocate Delays into Required Stan Format

allocate_empty() stable: Allocate Empty Parameters to a List

apply_default_cdf_cutoff(): Apply default CDF cutoff to a <dist_spec> if it is unconstrained

apply_tolerance() deprecated: Applies a threshold to all nonparametric distributions in a <dist_spec>

check_generation_time() stable: Validate probability distribution for using as generation time

check_reports_valid() stable: Validate data input

check_sparse_pmf_tail(): Check that PMF tail is not sparse

check_stan_delay() stable: Validate probability distribution for passing to stan

construct_output() stable: Construct Output

convert_to_natural() experimental: Internal function for converting parameters to natural parameters.

copy_results_to_latest() questioning: Copy Results From Dated Folder to Latest

create_backcalc_data() stable: Create Back Calculation Data

create_delay_inits(): Create initial conditions for delays

create_future_rt() stable: Construct the Required Future Rt assumption

create_gp_data() stable: Create Gaussian Process Data

create_initial_conditions() stable: Create Initial Conditions Generating Function

create_obs_model() stable: Create Observation Model Settings

create_rt_data() stable: Create Time-varying Reproduction Number Data

create_shifted_cases() stable: Create Delay Shifted Cases

create_stan_args() stable: Create a List of Stan Arguments

create_stan_data() stable: Create Stan Data Required for estimate_infections

create_stan_delays(): Create delay variables for stan

create_stan_params(): Create parameters for stan

default_fill_missing_obs() deprecated: Temporary function to support the transition to full support of missing data.

discrete_pmf() questioning: Discretised probability mass function

dist_skel() deprecated: Distribution Skeleton

epinow2_rstan_model(): Load an EpiNow2 rstan model.

epinow2_stan_model(): Return a stan model object for the appropriate backend

estimates_by_report_date() questioning: Estimate Cases by Report Date

extract_parameter() stable: Extract Samples for a Parameter from a Stan model

extract_parameter_samples() stable: Extract Parameter Samples from a Stan Model

extract_params() experimental: Extract parameter names

extract_single_dist() experimental: Extract a single element of a composite <dist_spec>

extract_static_parameter(): Extract Samples from a Parameter with a Single Dimension

fit_model(): Fit a model using the chosen backend.

fit_model_approximate() maturing: Fit a Stan Model using an approximate method

fit_model_with_nuts() maturing: Fit a Stan Model using the NUTs sampler

fix_dist() deprecated: Remove uncertainty in the parameters of a <dist_spec>

format_fit() stable: Format Posterior Samples

get_element(): Extracts an element of a <dist_spec>

get_raw_result() stable: Get a Single Raw Result

get_regions() stable: Get Folders with Results

get_regions_with_most_reports() stable: 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() experimental: Get the lower bounds of the parameters of a distribution

match_output_arguments() stable: Match User Supplied Arguments with Supported Options

natural_params() experimental: Get the names of the natural parameters of a distribution

ndist(): Calculate the number of distributions in a <dist_spec>

pad_reported_cases(): Pads reported cases with daily initial zeros

process_region() maturing: Process regional estimate

process_regions() stable: Process all Region Estimates

regional_runtimes() maturing: Summarise Regional Runtimes

save_estimate_infections() stable: Save Estimated Infections

save_input() stable: Save Observed Data

sd(<dist_spec>) experimental: Returns the standard deviation of one or more delay distribution

set_dt_single_thread(): Set to Single Threading

setup_dt() stable: Convert to Data Table

setup_target_folder() stable: Setup Target Folder for Saving

summarise_key_measures() maturing: Summarise rt and cases

summarise_results() questioning: Summarise Real-time Results

update_horizon() stable: Updates Forecast Horizon Based on Input Data and Target