ae_median_quantile: Absolute Error of the Median (Quantile-based Version)

View source: R/metrics_point_forecasts.R

ae_median_quantileR Documentation

Absolute Error of the Median (Quantile-based Version)

Description

Absolute error of the median calculated as

abs(true_value - median_prediction)

The function was created for internal use within score(), but can also used as a standalone function.

Usage

ae_median_quantile(true_values, predictions, quantiles = NULL)

Arguments

true_values

A vector with the true observed values of size n

predictions

numeric vector with predictions, corresponding to the quantiles in a second vector, quantiles.

quantiles

numeric vector that denotes the quantile for the values in predictions. Only those predictions where quantiles == 0.5 will be kept. If quantiles is NULL, then all predictions and true_values will be used (this is then the same as abs_error())

Value

vector with the scoring values

See Also

ae_median_sample(), abs_error()

Examples

true_values <- rnorm(30, mean = 1:30)
predicted_values <- rnorm(30, mean = 1:30)
ae_median_quantile(true_values, predicted_values, quantiles = 0.5)

scoringutils documentation built on May 14, 2022, 1:06 a.m.