Package index • epidist

Simulation

Tools for simulating datasets

simulate_double_censored_pmf(): Simulate a censored PMF

simulate_exponential_cases(): Simulate exponential cases

simulate_gillespie(): Simulate cases from a stochastic SIR model

simulate_secondary(): Simulate secondary events based on a delay distribution

simulate_uniform_cases(): Simulate cases from a uniform distribution

Preprocess

Functions for preprocessing observations

calculate_censor_delay(): Calculate the mean difference between continuous and discrete event time

combine_obs(): Combine truncated and fully observed observations

construct_cases_by_obs_window(): Construct case counts by observation window based on secondary observations

event_to_incidence(): Convert from event based to incidence based data

linelist_to_cases(): Convert primary and secondary observations to counts in long format

linelist_to_counts(): For a target variable convert from individual data to counts

reverse_obs_at(): For the observation observed at variable reverse the factor ordering

Observe

Functions for observing data

drop_zero(): Drop zero observations as unstable in a lognormal distribution

filter_obs_by_obs_time(): Filter observations based on a observation time of secondary events

filter_obs_by_ptime(): Filter observations based on the observation time of primary events

observe_process(): Observation process for primary and secondary events

pad_zero(): Pad zero observations as unstable in a lognormal distribution

S3 generics

S3 generics for delay modelling

epidist(): Interface using brms

epidist_family(): Define model specific family

epidist_formula(): Define a model specific formula

epidist_prepare(): Default method used when preparing data

epidist_prior(): Define model specific priors

epidist_stancode(): Define model specific Stan code

Method default

Default methods for S3 generics

epidist(<default>): Default method used for interface using brms

epidist_family(<default>): Default method for defining a model specific family

epidist_formula(<default>): Default method for defining a model specific formula

epidist_prepare(): Default method used when preparing data

epidist_prior(<default>): Default method for defining model specific priors

epidist_stancode(<default>): Default method for defining model specific Stan code

Latent individual model

Specific methods for the latent individual model

epidist_formula(<epidist_latent_individual>): Define a formula for the latent_individual model

epidist_prior(<epidist_latent_individual>): Define priors for the model

Postprocess

Functions for postprocessing model output

add_natural_scale_mean_sd(): Add natural scale summary parameters for a lognormal distribution

correct_primary_censoring_bias(): Primary event bias correction

draws_to_long(): Convert posterior lognormal samples to long format

extract_epinowcast_draws(): Extract posterior samples for a lognormal epinowcast model

extract_lognormal_draws(): Extract posterior samples for a lognormal brms model

make_relative_to_truth(): Make posterior lognormal samples relative to true values

sample_epinowcast_model(): Sample from the posterior of an epinowcast model with additional diagnositics

sample_model(): Sample from the posterior of a model with additional diagnositics

summarise_draws(): Summarise posterior draws

summarise_variable(): Summarise a variable

Plot

Functions and helper functions for plotting

calculate_cohort_mean(): Calculate the cohort-based or cumulative mean

calculate_truncated_means(): Calculate the truncated mean by observation horizon

plot_cases_by_obs_window(): Plot cases by observation window

plot_censor_delay(): Plot the mean difference between continuous and discrete event time

plot_cohort_mean(): Plot empirical cohort-based or cumulative mean

plot_empirical_delay(): Plot the empirical delay distribution

plot_mean_posterior_pred(): plot empirical cohort-based or cumulative mean vs posterior mean

plot_recovery(): Plot the posterior estimates as densities

plot_relative_recovery(): Plot the relative difference between true values and posterior estimates

Data

Data included with the package

sierra_leone_ebola_data: Ebola linelist data from Fang et al. (2016)

Utility functions

epidist_stan_chunk(): Read in a epidist Stan code chunk

epidist_version_stanvar(): Label a epidist Stan model with a version indicator