se_mean_sample {scoringutils} | R Documentation |
Squared error of the mean (sample-based version)
Description
Squared error of the mean calculated as
\textrm{mean}(\textrm{observed} - \textrm{mean prediction})^2
The mean prediction is calculated as the mean of the predictive samples.
Usage
se_mean_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, |
Input format
Overview of required input format for sample-based forecasts
Examples
observed <- rnorm(30, mean = 1:30)
predicted_values <- matrix(rnorm(30, mean = 1:30))
se_mean_sample(observed, predicted_values)
[Package scoringutils version 2.1.0 Index]