get_metrics.forecast_quantile {scoringutils}R Documentation

Get default metrics for quantile-based forecasts

Description

For quantile-based forecasts, the default scoring rules are:

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.

Usage

## S3 method for class 'forecast_quantile'
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

metrics-quantile.png

Overview of required input format for quantile-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_sample(), get_metrics.scores()

Examples

get_metrics(example_quantile, select = "wis")

[Package scoringutils version 2.0.0 Index]