Skip to contents

Create a forecast object for point forecasts

Source: R/class-forecast-point.R, R/class-forecast-quantile.R
as_forecast_point.Rd

When converting a forecast_quantile object into a forecast_point object, the 0.5 quantile is extracted and returned as the point forecast.

Usage

as_forecast_point(data, ...)

# Default S3 method
as_forecast_point(
  data,
  forecast_unit = NULL,
  observed = NULL,
  predicted = NULL,
  ...
)

# S3 method for class 'forecast_quantile'
as_forecast_point(data, ...)

Arguments

data

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

...

Unused

forecast_unit

(optional) Name of the columns in data (after any renaming of columns) that denote the unit of a single forecast. See get_forecast_unit() for details. If NULL (the default), all columns that are not required columns are assumed to form the unit of a single forecast. If specified, all columns that are not part of the forecast unit (or required columns) will be removed.

observed

(optional) Name of the column in data that contains the observed values. This column will be renamed to "observed".

predicted

(optional) Name of the column in data that contains the predicted values. This column will be renamed to "predicted".

Value

A forecast object of class forecast_point

Target format

The input for all further scoring needs to be a data.frame or similar with the following columns:

  • observed: Column of type numeric with observed values.

  • predicted: Column of type numeric with predicted values.

For convenience, we recommend an additional column model holding the name of the forecaster or model that produced a prediction, but this is not strictly necessary.

See the example_point data set for an example.

See also

Other functions to create forecast objects: as_forecast_binary(), as_forecast_multivariate_sample(), as_forecast_nominal(), as_forecast_ordinal(), as_forecast_quantile(), as_forecast_sample()