extra details for symmetrize

Author: dsweber2

R/arx_forecaster.R

@@ -268,10 +268,13 @@ arx_fcast_epi_workflow <- function(
 #' @param quantile_levels Vector or `NULL`. A vector of probabilities to produce
 #'   prediction intervals. These are created by computing the quantiles of
 #'   training residuals. A `NULL` value will result in point forecasts only.
-#' @param symmetrize Logical. The default `TRUE` calculates
-#'   symmetric prediction intervals. This argument only applies when
-#'   residual quantiles are used. It is not applicable with
-#'   `trainer = quantile_reg()`, for example.
+#' @param symmetrize Logical. The default `TRUE` calculates symmetric prediction
+#'   intervals. This argument only applies when residual quantiles are used. It
+#'   is not applicable with `trainer = quantile_reg()`, for example. This is
+#'   achieved by including both the residuals and their negation. Typically, one
+#'   would only want non-symmetric quantiles when increasing trajectories are
+#'   quite different from decreasing ones, such as a strictly postive variable
+#'   near zero.
 #' @param nonneg Logical. The default `TRUE` enforces nonnegative predictions
 #'   by hard-thresholding at 0.
 #' @param quantile_by_key Character vector. Groups residuals by listed keys

R/layer_residual_quantiles.R

@@ -10,7 +10,11 @@
 #' @param quantile_levels numeric vector of probabilities with values in (0,1)
 #'   referring to the desired quantile. Note that 0.5 will always be included
 #'   even if left out by the user.
-#' @param symmetrize logical. If `TRUE` then interval will be symmetric.
+#' @param symmetrize logical. If `TRUE` then the interval will be symmetric.
+#'   This is achieved by including both the residuals and their negations.
+#'   Typically, one would only want non-symmetric quantiles when increasing
+#'   trajectories are quite different from decreasing ones, such as a strictly
+#'   postive variable near zero.
 #' @param by_key A character vector of keys to group the residuals by before
 #'   calculating quantiles. The default, `c()` performs no grouping.
 #' @param name character. The name for the output column.
@@ -96,7 +100,7 @@ slather.layer_residual_quantiles <-
       return(components)
     }
 
-    s <- ifelse(object$symmetrize, -1, NA)
+    symmetric <- ifelse(object$symmetrize, -1, NA)
     r <- grab_residuals(the_fit, components)
 
     ## Handle any grouping requests
@@ -131,7 +135,7 @@ slather.layer_residual_quantiles <-
 
     r <- r %>%
       summarize(dstn = quantile_pred(matrix(quantile(
-        c(.resid, s * .resid),
+        c(.resid, symmetric * .resid),
         probs = object$quantile_levels, na.rm = TRUE
       ), nrow = 1), quantile_levels = object$quantile_levels))
     # Check for NA

man/arx_args_list.Rd

@@ -264,16 +264,16 @@ This is a different method of generating a flatline forecast, used as a baseline
 for [COVID19ForecastHub](https://covid19forecasthub.org).
 
 ```{r make-cdc-forecast, warning=FALSE}
-all_cdc_flatline <- 
-cdc_baseline_forecaster(
-  covid_case_death_rates |>
-    filter(time_value <= forecast_date, geo_value %in% used_locations),
-  outcome = "death_rate",
-  args_list = cdc_baseline_args_list(
-    aheads = 1:28,
-    data_frequency = "1 day"
+all_cdc_flatline <-
+  cdc_baseline_forecaster(
+    covid_case_death_rates |>
+      filter(time_value <= forecast_date, geo_value %in% used_locations),
+    outcome = "death_rate",
+    args_list = cdc_baseline_args_list(
+      aheads = 1:28,
+      data_frequency = "1 day"
+    )
   )
-)
 # same plotting code as in the arx multi-ahead case
 workflow <- all_cdc_flatline$epi_workflow
 results <- all_cdc_flatline$predictions