Get default metrics for multivariate point forecasts

For multivariate point forecasts, the default scoring rule is:

• "variogram_score" = variogram_score_multivariate_point()

Usage

# S3 method for class 'forecast_multivariate_point'
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 binary and point forecasts

See also

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

Examples

data <- data.frame(
  observed = c(1, 2, 3),
  predicted = c(1.1, 2.2, 3.3),
  target = c("a", "b", "c"),
  model = "m1",
  date = "2020-01-01"
)
ex <- as_forecast_multivariate_point(
  data,
  forecast_unit = c("model", "date", "target"),
  joint_across = "target"
)
get_metrics(ex)
#> $variogram_score
#> function (observed, predicted, mv_group_id, w_vs = NULL, p = 0.5) 
#> {
#>     assert_numeric(observed, min.len = 1)
#>     assert_numeric(as.vector(predicted), min.len = 1)
#>     assert_numeric(mv_group_id, len = length(observed))
#>     variogram_score_multivariate(observed = observed, predicted = predicted, 
#>         mv_group_id = mv_group_id, w = NULL, w_vs = w_vs, p = p)
#> }
#> <bytecode: 0x55c79fa7d298>
#> <environment: namespace:scoringutils>
#>