get_metrics.forecast_binary: Get default metrics for binary forecasts

In epiforecasts/scoringutils: Utilities for Scoring and Assessing Predictions

Get default metrics for binary forecasts

Description

For binary forecasts, the default scoring rules are:

• "brier_score" = brier_score()

• "log_score" = logs_binary()

Usage

## S3 method for class 'forecast_binary'
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

Value

A list of scoring functions.

Input format

Overview of required input format for binary and point forecasts

See Also

Other get_metrics functions: get_metrics(), get_metrics.forecast_nominal(), get_metrics.forecast_point(), get_metrics.forecast_quantile(), get_metrics.forecast_sample(), get_metrics.scores()

Examples

get_metrics(example_binary)
get_metrics(example_binary, select = "brier_score")
get_metrics(example_binary, exclude = "log_score")

epiforecasts/scoringutils documentation built on Nov. 6, 2024, 8:49 a.m.