scoringutils (version 2.1.0)

assert_forecast.forecast_binary: Assert that input is a forecast object and passes validations

Description

Assert that an object is a forecast object (i.e. a data.table with a class forecast and an additional class forecast_<type> corresponding to the forecast type).

See the corresponding assert_forecast_<type> functions for more details on the required input formats.

Usage

# S3 method for forecast_binary
assert_forecast(forecast, forecast_type = NULL, verbose = TRUE, ...)
# S3 method for forecast_point
assert_forecast(forecast, forecast_type = NULL, verbose = TRUE, ...)
# S3 method for forecast_quantile
assert_forecast(forecast, forecast_type = NULL, verbose = TRUE, ...)
# S3 method for forecast_sample
assert_forecast(forecast, forecast_type = NULL, verbose = TRUE, ...)
assert_forecast(forecast, forecast_type = NULL, verbose = TRUE, ...)
# S3 method for default
assert_forecast(forecast, forecast_type = NULL, verbose = TRUE, ...)

Value

Returns NULL invisibly.

Arguments

forecast

A forecast object (a validated data.table with predicted and observed values).

forecast_type

(optional) The forecast type you expect the forecasts to have. If the forecast type as determined by scoringutils based on the input does not match this, an error will be thrown. If NULL (the default), the forecast type will be inferred from the data.

verbose

Logical. If FALSE (default is TRUE), no messages and warnings will be created.

...

Currently unused. You cannot pass additional arguments to scoring functions via .... See the Customising metrics section below for details on how to use purrr::partial() to pass arguments to individual metrics.

Examples

forecast <- as_forecast_binary(example_binary)
assert_forecast(forecast)