A new R package for evaluation of probabilistic forecasts based on locally scale invariant proper scoring rules

Abstract

It is common to make predictions in the form of probabilistic forecasts in areas such as weather forecasting. Proper scoring rules are the standard way to evaluate these predictions. We implement a newly proposed proper scoring rule, which has some desirable properties, in an R package. We then use it to compare different fitted models with real data.