get_forecast_unit: Get unit of a single forecast

In epiforecasts/scoringutils: Utilities for Scoring and Assessing Predictions

Get unit of a single forecast

Description

Helper function to get the unit of a single forecast, i.e. the column names that define where a single forecast was made for. This just takes all columns that are available in the data and subtracts the columns that are protected, i.e. those returned by get_protected_columns() as well as the names of the metrics that were specified during scoring, if any.

Usage

get_forecast_unit(data)

Arguments

data	A data.frame (or similar) with predicted and observed values. See the details section of as_forecast() for additional information on required input formats.

Value

A character vector with the column names that define the unit of a single forecast

Forecast unit

In order to score forecasts, scoringutils needs to know which of the rows of the data belong together and jointly form a single forecasts. This is easy e.g. for point forecast, where there is one row per forecast. For quantile or sample-based forecasts, however, there are multiple rows that belong to single forecast.

The forecast unit or unit of a single forecast is then described by the combination of columns that uniquely identify a single forecast. For example, we could have forecasts made by different models in various locations at different time points, each for several weeks into the future. The forecast unit could then be described as forecast_unit = c("model", "location", "forecast_date", "forecast_horizon"). scoringutils automatically tries to determine the unit of a single forecast. It uses all existing columns for this, which means that no columns must be present that are unrelated to the forecast unit. As a very simplistic example, if you had an additional row, "even", that is one if the row number is even and zero otherwise, then this would mess up scoring as scoringutils then thinks that this column was relevant in defining the forecast unit.

In order to avoid issues, we recommend setting the forecast unit explicitly, usually through the forecast_unit argument in as_forecast(). This will drop unneeded columns, while making sure that all necessary, 'protected columns' like "predicted" or "observed" are retained.

epiforecasts/scoringutils documentation built on April 23, 2024, 4:56 p.m.