rename flatline / internal docs

Author: dajmcdon

NAMESPACE

@@ -80,7 +80,7 @@ export(extract_layers)
 export(extrapolate_quantiles)
 export(flatline)
 export(flatline_args_list)
-export(flatline_epi_forecaster)
+export(flatline_forecaster)
 export(frosting)
 export(get_test_data)
 export(grab_names)

R/flatline.R

@@ -10,7 +10,7 @@
 #'   horizon. The right hand side must contain any keys (locations) for the
 #'   panel data separated by plus. The observed time series must come last.
 #'   For example
-#'   ```
+#'   ```r
 #'   form <- as.formula(lead7_y ~ state + age + y)
 #'   ```
 #'   Note that this function doesn't DO the shifting, that has to be done
@@ -26,6 +26,7 @@
 #'   predictions for future data (the last observed of the outcome for each
 #'   combination of keys.
 #' @export
+#' @keywords internal
 #'
 #' @examples
 #' tib <- data.frame(y = runif(100),

R/flatline_epi_forecaster.R renamed to R/flatline_forecaster.R

@@ -26,10 +26,10 @@
 #' jhu <- case_death_rate_subset %>%
 #'   dplyr::filter(time_value >= as.Date("2021-12-01"))
 #'
-#' out <- flatline_epi_forecaster(jhu, "death_rate")
-flatline_epi_forecaster <- function(epi_data,
-                                    outcome,
-                                    args_list = flatline_args_list()) {
+#' out <- flatline_forecaster(jhu, "death_rate")
+flatline_forecaster <- function(epi_data,
+                                outcome,
+                                args_list = flatline_args_list()) {
 
   validate_forecaster_inputs(epi_data, outcome, "time_value")
   keys <- epi_keys(epi_data)
@@ -71,7 +71,7 @@ flatline_epi_forecaster <- function(epi_data,
 
 #' Flatline forecaster argument constructor
 #'
-#' Constructs a list of arguments for [flatline_epi_forecaster()].
+#' Constructs a list of arguments for [flatline_forecaster()].
 #'
 #' @inheritParams arx_args_list
 #'

man/flatline.Rd

@@ -328,7 +328,7 @@ But ideally, a user could create their own forecasters by building up the
 components we provide. In other vignettes, we try to walk through some of these
 customizations.
 
-To illustrate everything above, here is (roughly) the code for the `flatline_epi_forecaster()` applied to the `case_rate`.
+To illustrate everything above, here is (roughly) the code for the `flatline_forecaster()` applied to the `case_rate`.
 
 ```{r}
 r <- epi_recipe(jhu) %>%