Absolute error of the median (sample-based version)

Absolute error of the median calculated as

$$% \textrm{abs}(\textrm{observevd} - \textrm{median\_prediction}) $$

Usage

ae_median_sample(observed, predicted)

Arguments

observed

A vector with observed values of size n

predicted

nxN matrix of predictive samples, n (number of rows) being the number of data points and N (number of columns) the number of Monte Carlo samples. Alternatively, predicted can just be a vector of size n.

Value

vector with the scoring values

Input format

See also

ae_median_quantile()

Examples

observed <- rnorm(30, mean = 1:30)
predicted_values <- matrix(rnorm(30, mean = 1:30))
ae_median_sample(observed, predicted_values)
#>  [1] 1.61022189 0.32735036 2.52982645 0.98458168 0.94495454 0.65538891
#>  [7] 0.56511146 0.09373061 1.31110818 0.61226219 0.75386115 0.08959962
#> [13] 0.39077113 1.56818369 0.84567980 1.24260044 0.27781917 0.65054779
#> [19] 1.18084954 0.45036469 0.05976767 0.14675942 0.60583332 0.19442459
#> [25] 0.21123533 0.28585022 0.64582375 1.78993469 1.20347916 0.67902801