metrics_quantile: Default metrics and scoring rules for quantile-based...

In epiforecasts/scoringutils: Utilities for Scoring and Assessing Predictions

Default metrics and scoring rules for quantile-based forecasts

Description

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.

Usage

metrics_quantile(select = NULL, exclude = NULL)

Arguments

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.

Value

A list of scoring functions.

Input format

Examples

metrics_quantile()
metrics_quantile(select = "wis")

epiforecasts/scoringutils documentation built on Aug. 20, 2024, 9:58 p.m.