Helper function that prints the output generated by
check_forecasts()
Usage
# S3 method for scoringutils_check
print(x, ...)Arguments
- x
An object of class 'scoringutils_check' as produced by
check_forecasts()- ...
additional arguments (not used here)
Examples
check <- check_forecasts(example_quantile)
#> The following messages were produced when checking inputs:
#> 1. 144 values for `prediction` are NA in the data provided and the corresponding rows were removed. This may indicate a problem if unexpected.
print(check)
#> Your forecasts seem to be for a target of the following type:
#> $target_type
#> [1] "integer"
#>
#> and in the following format:
#> $prediction_type
#> [1] "quantile"
#>
#> The unit of a single forecast is defined by:
#> $forecast_unit
#> [1] "location" "target_end_date" "target_type" "location_name"
#> [5] "forecast_date" "model" "horizon"
#>
#> Cleaned data, rows with NA values in prediction or true_value removed:
#> $cleaned_data
#> location target_end_date target_type true_value location_name
#> 1: DE 2021-05-08 Cases 106987 Germany
#> 2: DE 2021-05-08 Cases 106987 Germany
#> 3: DE 2021-05-08 Cases 106987 Germany
#> 4: DE 2021-05-08 Cases 106987 Germany
#> 5: DE 2021-05-08 Cases 106987 Germany
#> ---
#> 20397: IT 2021-07-24 Deaths 78 Italy
#> 20398: IT 2021-07-24 Deaths 78 Italy
#> 20399: IT 2021-07-24 Deaths 78 Italy
#> 20400: IT 2021-07-24 Deaths 78 Italy
#> 20401: IT 2021-07-24 Deaths 78 Italy
#> forecast_date quantile prediction model horizon
#> 1: 2021-05-03 0.010 82466 EuroCOVIDhub-ensemble 1
#> 2: 2021-05-03 0.025 86669 EuroCOVIDhub-ensemble 1
#> 3: 2021-05-03 0.050 90285 EuroCOVIDhub-ensemble 1
#> 4: 2021-05-03 0.100 95341 EuroCOVIDhub-ensemble 1
#> 5: 2021-05-03 0.150 99171 EuroCOVIDhub-ensemble 1
#> ---
#> 20397: 2021-07-12 0.850 352 epiforecasts-EpiNow2 2
#> 20398: 2021-07-12 0.900 397 epiforecasts-EpiNow2 2
#> 20399: 2021-07-12 0.950 499 epiforecasts-EpiNow2 2
#> 20400: 2021-07-12 0.975 611 epiforecasts-EpiNow2 2
#> 20401: 2021-07-12 0.990 719 epiforecasts-EpiNow2 2
#>
#> Number of unique values per column per model:
#> $unique_values
#> model location target_end_date target_type true_value
#> 1: EuroCOVIDhub-ensemble 4 12 2 96
#> 2: EuroCOVIDhub-baseline 4 12 2 96
#> 3: epiforecasts-EpiNow2 4 12 2 95
#> 4: UMass-MechBayes 4 12 1 48
#> location_name forecast_date quantile prediction horizon
#> 1: 4 11 23 3969 3
#> 2: 4 11 23 3733 3
#> 3: 4 11 23 3903 3
#> 4: 4 11 23 1058 3
#>
#> $messages
#> [1] "144 values for `prediction` are NA in the data provided and the corresponding rows were removed. This may indicate a problem if unexpected."
#>