Package index • epidist

Data preparation

Linelist data

Functions for preparing linelist data

as_epidist_linelist_data(): Create an epidist_linelist_data object
as_epidist_linelist_data(<data.frame>): Create an epidist_linelist_data object from a data frame with event dates
as_epidist_linelist_data(<default>): Create an epidist_linelist_data object from vectors of event times
as_epidist_linelist_data(<epidist_aggregate_data>): Convert aggregate data to linelist format
assert_epidist(<epidist_linelist_data>): Assert validity of epidist_linelist_data objects
is_epidist_linelist_data(): Check if data has the epidist_linelist_data class
new_epidist_linelist_data(): Class constructor for epidist_linelist_data objects

Aggregate data

Functions for preparing aggregate data

as_epidist_aggregate_data(): Create an epidist_aggregate_data object
as_epidist_aggregate_data(<data.frame>): Create an epidist_aggregate_data object from a data.frame
as_epidist_aggregate_data(<default>): Create an epidist_aggregate_data object from vectors of event times
as_epidist_aggregate_data(<epidist_linelist_data>): Convert linelist data to aggregate format
assert_epidist(<epidist_aggregate_data>): Assert validity of epidist_aggregate_data objects
is_epidist_aggregate_data(): Check if data has the epidist_aggregate_data class
new_epidist_aggregate_data(): Class constructor for epidist_aggregate_data objects

Class methods

Methods that keep modified objects in their epidist class

`[`(<epidist_data>) `[<-`(<epidist_data>) `[[<-`(<epidist_data>) `$<-`(<epidist_data>) `names<-`(<epidist_data>) rbind(<epidist_data>) dplyr_reconstruct(<epidist_data>) dplyr_row_slice(<epidist_data>) dplyr_col_modify(<epidist_data>) group_by(<epidist_data>) ungroup(<epidist_data>): Keep epidist objects in their class
is_epidist_data(): Check if data has the epidist_data class

Estimates data

Functions for preparing published summary estimates

as_epidist_estimates_data(): Create an epidist_estimates_data object
as_epidist_estimates_data(<data.frame>): Create an epidist_estimates_data object from a data frame
as_epidist_estimates_data(<epidist_estimates_data>): Return an epidist_estimates_data object unchanged
as_epidist_estimates_data(<epidist_multivariate>): Create an epidist_estimates_data object from a multivariate representation
as_epidist_estimates_data(<list>): Combine epidist_estimates_data objects from several studies
assert_epidist(<epidist_estimates_data>): Assert validity of epidist_estimates_data objects
epidist_estimates_epireview(): Report studies from an epireview parameter table
epidist_estimates_parameters(): Report a study that published the parameters of a distribution it fitted
epidist_estimates_summaries(): Report a study that published summaries of its delays
is_epidist_estimates_data(): Check if data has the epidist_estimates_data class
new_epidist_estimates_data(): Class constructor for epidist_estimates_data objects

Multivariate representation

Functions for representing draws of a set of parameters

as_epidist_multivariate(): Create an epidist_multivariate object
as_epidist_multivariate(<data.frame>): Create an epidist_multivariate object from a data frame of draws
as_epidist_multivariate(<matrix>): Create an epidist_multivariate object from a matrix of draws
assert_epidist(<epidist_multivariate>): Assert validity of epidist_multivariate objects
is_epidist_multivariate(): Check if an object has the epidist_multivariate class
new_epidist_multivariate(): Class constructor for epidist_multivariate objects
print(<epidist_multivariate>): Print an epidist_multivariate object
vcov(<epidist_multivariate>): The covariance matrix of an epidist_multivariate object

Models

Naive model

Specific methods for the naive model

as_epidist_naive_model(): Convert an object to an epidist_naive_model object
as_epidist_naive_model(<epidist_aggregate_data>): The naive model method for epidist_aggregate_data objects
as_epidist_naive_model(<epidist_linelist_data>): The naive model method for epidist_linelist_data objects
epidist_formula_model(<epidist_naive_model>): Define the model-specific component of an epidist custom formula for the naive model
epidist_newdata(<epidist_naive_model>): Build newdata for the naive model
epidist_transform_data_model(<epidist_naive_model>): Transform data for the naive model
is_epidist_naive_model(): Check if data has the epidist_naive_model class
new_epidist_naive_model(): Class constructor for epidist_naive_model objects

Latent model

Specific methods for the latent model

as_epidist_latent_model(): Convert an object to an epidist_latent_model object
as_epidist_latent_model(<epidist_aggregate_data>): The latent model method for epidist_aggregate_data objects
as_epidist_latent_model(<epidist_linelist_data>): The latent model method for epidist_linelist_data objects
epidist_family_model(<epidist_latent_model>): Create the model-specific component of an epidist custom family
epidist_formula_model(<epidist_latent_model>): Define the model-specific component of an epidist custom formula for the latent model
epidist_model_prior(<epidist_latent_model>): Model specific prior distributions for latent models
epidist_newdata(<epidist_latent_model>): Build newdata for the latent model
is_epidist_latent_model(): Check if data has the epidist_latent_model class
new_epidist_latent_model(): Class constructor for epidist_latent_model objects

Marginal model

Specific methods for the marginal model

as_epidist_marginal_model(): Convert an object to an epidist_marginal_model object
as_epidist_marginal_model(<epidist_aggregate_data>): The marginal model method for epidist_aggregate_data objects
as_epidist_marginal_model(<epidist_linelist_data>): The marginal model method for epidist_linelist_data objects
epidist_family_model(<epidist_marginal_model>): Create the model-specific component of an epidist custom family
epidist_formula_model(<epidist_marginal_model>): Define the model-specific component of an epidist custom formula for the marginal model
epidist_newdata(<epidist_marginal_model>): Build newdata for the marginal model
epidist_transform_data_model(<epidist_marginal_model>): Transform data for the marginal model
is_epidist_marginal_model(): Check if data has the epidist_marginal_model class
new_epidist_marginal_model(): Class constructor for epidist_marginal_model objects

Meta model

Specific methods for the meta model

as_epidist_meta_model(<NULL>): The meta model method for summary estimates only
as_epidist_meta_model(): Convert an object to an epidist_meta_model object
as_epidist_meta_model(<epidist_aggregate_data>): The meta model method for epidist_aggregate_data objects
as_epidist_meta_model(<epidist_estimates_data>): The meta model method for epidist_estimates_data objects
as_epidist_meta_model(<epidist_linelist_data>): The meta model method for epidist_linelist_data objects
assert_epidist(<epidist_meta_model>): Assert validity of epidist_meta_model objects
epidist_family_model(<epidist_meta_model>): Create the model-specific component of an epidist custom family
epidist_formula_model(<epidist_meta_model>): Define the model-specific component of an epidist custom formula for the meta model
epidist_model_prior(<epidist_meta_model>): Model specific prior distributions for the meta model
epidist_newdata(<epidist_meta_model>): Build newdata for the meta model
epidist_transform_data_model(<epidist_meta_model>): Transform data for the meta model
is_epidist_meta_model(): Check if data has the epidist_meta_model class
new_epidist_meta_model(): Class constructor for epidist_meta_model objects

Model fitting

Functions for fitting delay distribution models using brms

epidist(): Fit epidemiological delay distributions using a brms interface

Prediction data

Functions for building newdata to predict from

epidist_newdata(): Build newdata for prediction from an epidist data object
epidist_newdata(<default>): Default method for building newdata
epidist_newdata(<epidist_latent_model>): Build newdata for the latent model
epidist_newdata(<epidist_marginal_model>): Build newdata for the marginal model
epidist_newdata(<epidist_meta_model>): Build newdata for the meta model
epidist_newdata(<epidist_naive_model>): Build newdata for the naive model

Postprocess

Functions for postprocessing model output

add_summaries(): Add natural scale summaries of the delay distribution
delay_parameter_draws() add_delay_parameter_draws(): Posterior draws of the delay distribution parameters
delay_summary_draws(): Posterior draws of the delay distribution, summarised
`[`(<epidist_delay_draws>) `names<-`(<epidist_delay_draws>) dplyr_reconstruct(<epidist_delay_draws>) dplyr_row_slice(<epidist_delay_draws>) dplyr_col_modify(<epidist_delay_draws>) group_by(<epidist_delay_draws>) ungroup(<epidist_delay_draws>): Keep the epidist_delay_draws class through dplyr verbs
epidist_strata(): Unique combinations of the predictors in a model

Diagnostic functions

epidist_diagnostics(): Diagnostics for epidist_fit models

Plotting

Functions for plotting data and posterior draws

plot(<epidist_delay_draws>) autoplot(<epidist_delay_draws>): Plot posterior draws of the delay distribution
plot_events(): Plot the primary and secondary event windows of each case

Model specification

Family

Functions related to specifying custom brms families

epidist_family(): Define epidist family
epidist_family_model(): The model-specific parts of an epidist_family() call
epidist_family_model(<default>): Default method for defining a model specific family
epidist_family_param(<default>): Default method for families which do not require a reparameterisation

Formula

Functions related to specifying custom brms formula

epidist_formula(): Define a model specific formula
epidist_formula_model(): The model-specific parts of an epidist_formula() call
epidist_formula_model(<default>): Default method for defining a model specific formula

Prior distributions

Functions for specifying prior distributions

epidist_family_prior(): Family specific prior distributions
epidist_family_prior(<default>): Default family specific prior distributions
epidist_family_prior(<lognormal>): Family specific prior distributions for the lognormal family
epidist_model_prior(): Model specific prior distributions
epidist_model_prior(<default>): Default model specific prior distributions
epidist_model_prior(<epidist_meta_model>): Model specific prior distributions for the meta model
epidist_prior(): Define custom prior distributions for epidist models

Stan code

Functions for specifying custom Stan code to put into brms

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

Package internals

Transform data

Transform data using the formula and family information

epidist_transform_data_model(): The model-specific parts of an epidist_transform_data() call
epidist_transform_data_model(<default>): Default method for transforming data for a model

Generator model functions

Generator functions for creating family specific model utilities.

epidist_gen_log_lik(): Create a function to calculate the marginalised log likelihood for double censored and truncated delay distributions
epidist_gen_meta_log_lik(): Create a function to calculate the meta model log likelihood
epidist_gen_meta_predict(): Create a function to draw from the meta model posterior predictive distribution
epidist_gen_posterior_epred(): Create a function to draw from the expected value of the posterior predictive distribution for a model
epidist_gen_posterior_predict(): Create a function to draw from the posterior predictive distribution for a double censored and truncated delay distribution

Assert validity of objects

Functions used to assert the validity of package objects

assert_epidist(): Validation for epidist objects

Simulation and Data

Simulation

Tools for simulating datasets

simulate_dates(): Convert simulated event times to dates
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_study(): Simulate the summaries a published study would have reported
simulate_uniform_cases(): Simulate cases from a uniform distribution

Data

Data included with the package

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

Reexported functions

reexports lognormal weibull Gamma bf: Objects exported from other packages