View source: R/default-scoring-rules.R
metrics_quantile | R Documentation |
Helper function that returns a named list of default scoring rules suitable for forecasts in a quantile-based format.
The default scoring rules are:
"wis" = wis
"overprediction" = overprediction_quantile()
"underprediction" = underprediction_quantile()
"dispersion" = dispersion_quantile()
"bias" = bias_quantile()
"interval_coverage_50" = interval_coverage()
"interval_coverage_90" = purrr::partial( interval_coverage, interval_range = 90 )
"interval_coverage_deviation" = interval_coverage_deviation()
,
"ae_median" = ae_median_quantile()
Note: The interval_coverage_90
scoring rule is created by modifying
interval_coverage()
, making use of the function purrr::partial()
.
This construct allows the function to deal with arbitrary arguments in ...
,
while making sure that only those that interval_coverage()
can
accept get passed on to it. interval_range = 90
is set in the function
definition, as passing an argument interval_range = 90
to score()
would
mean it would also get passed to interval_coverage_50
.
metrics_quantile(select = NULL, exclude = NULL)
select |
A character vector of scoring rules to select from the list. If
|
exclude |
A character vector of scoring rules to exclude from the list.
If |
A list of scoring functions.
metrics_quantile()
metrics_quantile(select = "wis")
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