Helper function to get the unit of a single forecast, i.e. the column names that define where a single forecast was made for
get_forecast_unit(data)A character vector with the column names that define the unit of a single forecast
A data.frame or data.table with the predictions and observations.
For scoring using score(), the following columns need to be present:
true_value - the true observed values
prediction - predictions or predictive samples for one
true value. (You only don't need to provide a prediction column if
you want to score quantile forecasts in a wide range format.)
For scoring integer and continuous forecasts a sample column is needed:
sample - an index to identify the predictive samples in the
prediction column generated by one model for one true value. Only
necessary for continuous and integer forecasts, not for
binary predictions.
For scoring predictions in a quantile-format forecast you should provide
a column called quantile:
quantile: quantile to which the prediction corresponds
In addition a model column is suggested and if not present this will be
flagged and added to the input data with all forecasts assigned as an
"unspecified model").
You can check the format of your data using check_forecasts() and there
are examples for each format (example_quantile, example_continuous,
example_integer, and example_binary).