From 0d12262957b1c3d3657c1919a3addda42cb3dcf5 Mon Sep 17 00:00:00 2001
From: nikosbosse <nikosbosse@gmail.com>
Date: Mon, 16 Sep 2024 18:30:38 +0200
Subject: [PATCH] fix docs

---
 R/score_model_out.R    | 14 ++++++++------
 man/score_model_out.Rd | 11 +++++------
 2 files changed, 13 insertions(+), 12 deletions(-)

diff --git a/R/score_model_out.R b/R/score_model_out.R
index 1b35f16..0fd3a29 100644
--- a/R/score_model_out.R
+++ b/R/score_model_out.R
@@ -16,15 +16,17 @@
 #' @details If `metrics` is `NULL` (the default), this function chooses
 #' appropriate metrics based on the `output_type` contained in the `model_out_tbl`:
 #'
-#' - For `output_type == "quantile"`, we use the default metrics provided by
+#' \itemize{
+#' \item For `output_type == "quantile"`, we use the default metrics provided by
 #' `scoringutils`:
 #' `r names(scoringutils::get_metrics(scoringutils::example_quantile))`
-#' - For `output_type == "pmf"` and `output_type_id_order` is `NULL` (indicating
+#' \item For `output_type == "pmf"` and `output_type_id_order` is `NULL` (indicating
 #' that the predicted variable is a nominal variable), we use the default metric
-#' provided by `scoringutils`:,
+#' provided by `scoringutils`:
 #' `r names(scoringutils::get_metrics(scoringutils::example_nominal))`
-#'   - For `output_type == "median"`, we use "ae_point"
-#'   - For `output_type == "mean"`, we use "se_point"
+#'   \item For `output_type == "median"`, we use "ae_point"
+#'   \item For `output_type == "mean"`, we use "se_point"
+#' }
 #'
 #' Alternatively, a character vector of scoring metrics can be provided. In this
 #' case, the following options are supported:
@@ -46,7 +48,7 @@
 #'   - `output_type == "pmf"`:
 #'     - "log_score": log score
 #'
-#' See [scoringutils::get_metrics()] for more details on the default meterics
+#' See [scoringutils::get_metrics()] for more details on the default metrics
 #' used by `scoringutils`.
 #'
 #' @examplesIf requireNamespace("hubExamples", quietly = TRUE)
diff --git a/man/score_model_out.Rd b/man/score_model_out.Rd
index 94fd2d0..64b1209 100644
--- a/man/score_model_out.Rd
+++ b/man/score_model_out.Rd
@@ -41,19 +41,18 @@ Score model output predictions with a single \code{output_type} against observed
 \details{
 If \code{metrics} is \code{NULL} (the default), this function chooses
 appropriate metrics based on the \code{output_type} contained in the \code{model_out_tbl}:
+
 \itemize{
 \item For \code{output_type == "quantile"}, we use the default metrics provided by
 \code{scoringutils}:
-\verb{r names(scoringutils::get_metrics(scoringutils::example_quantile))}
+wis, overprediction, underprediction, dispersion, bias, interval_coverage_50, interval_coverage_90, interval_coverage_deviation, ae_median
 \item For \code{output_type == "pmf"} and \code{output_type_id_order} is \code{NULL} (indicating
 that the predicted variable is a nominal variable), we use the default metric
-provided by \code{scoringutils}:,
-\verb{r names(scoringutils::get_metrics(scoringutils::example_nominal))}
-\itemize{
+provided by \code{scoringutils}:
+log_score
 \item For \code{output_type == "median"}, we use "ae_point"
 \item For \code{output_type == "mean"}, we use "se_point"
 }
-}
 
 Alternatively, a character vector of scoring metrics can be provided. In this
 case, the following options are supported:
@@ -83,7 +82,7 @@ based on quantiles at the probability levels 0.025 and 0.975.
 }
 }
 
-See \code{\link[scoringutils:get_metrics]{scoringutils::get_metrics()}} for more details on the default meterics
+See \code{\link[scoringutils:get_metrics]{scoringutils::get_metrics()}} for more details on the default metrics
 used by \code{scoringutils}.
 }
 \examples{