get_metrics.forecast_sample {scoringutils} | R Documentation |
Get default metrics for sample-based forecasts
Description
For sample-based forecasts, the default scoring rules are:
"crps" =
crps_sample()
"overprediction" =
overprediction_sample()
"underprediction" =
underprediction_sample()
"dispersion" =
dispersion_sample()
"log_score" =
logs_sample()
"dss" =
dss_sample()
"mad" =
mad_sample()
"bias" =
bias_sample()
"ae_median" =
ae_median_sample()
"se_mean" =
se_mean_sample()
Usage
## S3 method for class 'forecast_sample'
get_metrics(x, select = NULL, exclude = NULL, ...)
Arguments
x |
A forecast object (a validated data.table with predicted and
observed values, see |
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 |
... |
unused |
Input format
Overview of required input format for sample-based forecasts
See Also
Other get_metrics functions:
get_metrics()
,
get_metrics.forecast_binary()
,
get_metrics.forecast_nominal()
,
get_metrics.forecast_point()
,
get_metrics.forecast_quantile()
,
get_metrics.scores()
Examples
get_metrics(example_sample_continuous, exclude = "mad")