scoringutils (version 1.2.2)

logs_sample: Logarithmic score

Description

Wrapper around the logs_sample() function from the scoringRules package. Used to score continuous predictions. While the Log Score is in theory also applicable to integer forecasts, the problem lies in the implementation: The Log Score needs a kernel density estimation, which is not well defined with integer-valued Monte Carlo Samples. The Log Score can be used for specific integer valued probability distributions. See the scoringRules package for more details.

Usage

logs_sample(true_values, predictions)

Value

vector with the scoring values

Arguments

true_values

A vector with the true observed values of size n

predictions

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, predictions can just be a vector of size n.

References

Alexander Jordan, Fabian Krüger, Sebastian Lerch, Evaluating Probabilistic Forecasts with scoringRules, https://www.jstatsoft.org/article/view/v090i12

Examples

true_values <- rpois(30, lambda = 1:30)
predictions <- replicate(200, rpois(n = 30, lambda = 1:30))
logs_sample(true_values, predictions)