Get default metrics for sample-based forecasts

For sample-based multivariate forecasts, the default scoring rules are:

• "energy_score" = energy_score_multivariate()

Usage

# S3 method for class 'forecast_sample_multivariate'
get_metrics(x, select = NULL, exclude = NULL, ...)

Arguments

x

A forecast object (a validated data.table with predicted and observed values, see as_forecast_binary()).

select

A character vector of scoring rules to select from the list. If select is NULL (the default), all possible scoring rules are returned.

exclude

A character vector of scoring rules to exclude from the list. If select is not NULL, this argument is ignored.

...

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_ordinal(), get_metrics.forecast_point(), get_metrics.forecast_quantile(), get_metrics.forecast_sample(), get_metrics.scores()

Examples

example <- as_forecast_multivariate_sample(
  example_sample_continuous, joint_across = c("location", "location_name")
)
#> ℹ Some rows containing NA values may be removed. This is fine if not
#>   unexpected.
get_metrics(example)
#> $energy_score
#> function (observed, predicted, mv_group_id, w = NULL) 
#> {
#>     assert_input_multivariate_sample(observed, predicted, mv_group_id)
#>     unique_groups <- unique(mv_group_id)
#>     energy_score <- vapply(unique_groups, function(group) {
#>         idx <- which(mv_group_id == group)
#>         es_sample(y = observed[idx], dat = predicted[idx, , drop = FALSE], 
#>             w = w)
#>     }, numeric(1))
#>     names(energy_score) <- unique_groups
#>     return(energy_score)
#> }
#> <bytecode: 0x55c1892c8e78>
#> <environment: namespace:scoringutils>
#>