Document and lint, plus move default formula to delay ~ .

NAMESPACE

@@ -3,6 +3,7 @@
 S3method(add_mean_sd,default)
 S3method(add_mean_sd,gamma_samples)
 S3method(add_mean_sd,lognormal_samples)
+S3method(as_direct_model,data.frame)
 S3method(as_latent_individual,data.frame)
 S3method(epidist,default)
 S3method(epidist_family_model,default)
@@ -17,9 +18,11 @@ S3method(epidist_model_prior,default)
 S3method(epidist_stancode,default)
 S3method(epidist_stancode,epidist_latent_individual)
 S3method(epidist_validate,default)
+S3method(epidist_validate,epidist_direct_model)
 S3method(epidist_validate,epidist_latent_individual)
 export(add_event_vars)
 export(add_mean_sd)
+export(as_direct_model)
 export(as_latent_individual)
 export(epidist)
 export(epidist_diagnostics)
@@ -35,6 +38,7 @@ export(epidist_stancode)
 export(epidist_validate)
 export(filter_obs_by_obs_time)
 export(filter_obs_by_ptime)
+export(is_direct_model)
 export(is_latent_individual)
 export(observe_process)
 export(predict_delay_parameters)

R/direct_model.R

@@ -1,3 +1,8 @@
+#' Prepare direct model to pass through to `brms`
+#'
+#' @param data A `data.frame` containing line list data
+#' @family direct_model
+#' @export
 as_direct_model <- function(data) {
   UseMethod("as_direct_model")
 }
@@ -10,6 +15,21 @@ assert_direct_model_input <- function(data) {
   assert_numeric(data$stime, lower = 0)
 }
 
+#' Prepare latent individual model
+#'
+#' This function prepares data for use with the direct model. It does this by
+#' adding columns used in the model to the `data` object provided. To do this,
+#' the `data` must already have columns for the case number (integer),
+#' (positive, numeric) times for the primary and secondary event times. The
+#' output of this function is a `epidist_direct_model` class object, which may
+#' be passed to [epidist()] to perform inference for the model.
+#'
+#' @param data A `data.frame` containing line list data
+#' @rdname as_direct_model
+#' @method as_direct_model data.frame
+#' @family direct_model
+#' @autoglobal
+#' @export
 as_direct_model.data.frame <- function(data) {
   assert_direct_model_input(data)
   class(data) <- c("epidist_direct_model", class(data))
@@ -19,23 +39,30 @@ as_direct_model.data.frame <- function(data) {
   return(data)
 }
 
+#' Validate direct model data
+#'
+#' This function checks whether the provided `data` object is suitable for
+#' running the direct model. As well as making sure that
+#' `is_direct_model()` is true, it also checks that `data` is a `data.frame`
+#' with the correct columns.
+#'
+#' @param data A `data.frame` containing line list data
+#' @param ... ...
+#' @method epidist_validate epidist_direct_model
+#' @family direct_model
+#' @export
 epidist_validate.epidist_direct_model <- function(data, ...) {
   assert_true(is_direct_model(data))
   assert_direct_model_input(data)
   assert_names(names(data), must.include = c("case", "ptime", "stime", "delay"))
   assert_numeric(data$delay, lower = 0)
 }
 
+#' Check if data has the `epidist_direct_model` class
+#'
+#' @param data A `data.frame` containing line list data
+#' @family latent_individual
+#' @export
 is_direct_model <- function(data) {
   inherits(data, "epidist_direct_model")
 }
-
-epidist_formula_model.epidist_direct_model <- function(
-    data, formula, ...
-) {
-  # data is only used to dispatch on
-  formula <- stats::update(
-    formula, delay ~ .
-  )
-  return(formula)
-}

R/formula.R

@@ -41,5 +41,8 @@ epidist_formula_model <- function(data, formula, ...) {
 #' @family formula
 #' @export
 epidist_formula_model.default <- function(data, formula, ...) {
+  formula <- stats::update(
+    formula, delay ~ .
+  )
   return(formula)
 }