Why extend epidist?

epidist handles the parts of delay estimation that are tedious and easy to get wrong. Censoring, truncation, the brms formula interface, priors, and the Stan code that ties them together.

If you are building a model that shares those problems but has a different likelihood, you might want to do so by extending epidist.

Two packages already do this, in two different ways.

• cfrnow registers a new model type.
• tbl.now adds a new data source, by writing as_epidist_linelist_data() and as_epidist_aggregate_data() methods for its own class.

Adding a data source

Write a method that turns your class into one epidist understands.

#' @importFrom epidist as_epidist_linelist_data
#' @export
as_epidist_linelist_data.my_class <- function(data, ...) {
  return(as_epidist_linelist_data(
    as.data.frame(data),
    pdate_lwr = "onset_date",
    sdate_lwr = "report_date"
  ))
}

my_data |>
  as_epidist_linelist_data() |>
  as_epidist_marginal_model() |>
  epidist(formula = mu ~ 1)

Adding a model type

A model type is an S3 class plus methods for six generics.

Three you have to supply.

Three are optional.

You also write a constructor that sets your class, by convention as_epidist_<name>_model().

The skeleton looks like this.

as_epidist_my_model <- function(data) {
  class(data) <- c("epidist_my_model", class(data))
  assert_epidist(data)
  return(data)
}

#' @importFrom epidist assert_epidist
#' @export
assert_epidist.epidist_my_model <- function(data, ...) {
  checkmate::assert_names(names(data), must.include = c("delay", "n"))
  return(invisible(NULL))
}

#' @importFrom epidist epidist_family_model
#' @export
epidist_family_model.epidist_my_model <- function(data, family, ...) {
  return(brms::custom_family(
    paste0("my_model_", family$family),
    dpars = family$dpars,
    vars = "vreal1",
    loop = FALSE
  ))
}

#' @importFrom epidist epidist_formula_model
#' @export
epidist_formula_model.epidist_my_model <- function(data, formula, ...) {
  return(stats::update(formula, delay | vreal(n) ~ .))
}

#' @importFrom epidist epidist_stancode
#' @export
epidist_stancode.epidist_my_model <- function(data, family, formula, ...) {
  return(brms::stanvar(block = "functions", scode = "// your lpdf here"))
}

Register the S3 methods in your NAMESPACE and import the generics from epidist, as cfrnow does:

importFrom(epidist,assert_epidist)
importFrom(epidist,epidist_family_model)
importFrom(epidist,epidist_formula_model)
importFrom(epidist,epidist_stancode)
S3method(assert_epidist,epidist_my_model)
S3method(epidist_family_model,epidist_my_model)
S3method(epidist_formula_model,epidist_my_model)
S3method(epidist_stancode,epidist_my_model)

Users then call epidist() exactly as they would for a built-in model.

data |>
  as_epidist_my_model() |>
  epidist(formula = mu ~ 1)

Exploring how cfrnow extends epidist

cfrnow fits a mixture-cure survival model to estimate a real-time case fatality ratio. Every method it needs is in R/cure_model.R.

cfrnow also exports its own frontend. Its users call prepare_cfr_data(), fit_cfr() and pp_check_cfr() rather than epidist().

Getting help

If you are building an extension and something in this interface is awkward, please open an issue.