logs: LogS

In nikosbosse/scoringutils2:

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 probabiliy distributions. See the scoringRules package for more details.

Usage

logs(true_values, predictions)

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

Value

vector with the scoring values

References

Alexander Jordan, Fabian Krüger, Sebastian Lerch, Evaluating Probabilistic Forecasts withscoringRules, https://arxiv.org/pdf/1709.04743.pdf

Examples

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

nikosbosse/scoringutils2 documentation built on Jan. 8, 2021, 12:12 p.m.