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Probabilistic forecasts in the form of probability distributions over futureevents have become popular in several fields including meteorology, hydrology,economics, and demography. In typical applications, many alternativestatistical models and data sources can be used to produce probabilisticforecasts. Hence, evaluating and selecting among competing methods is animportant task. The scoringRules package for R provides functionality forcomparative evaluation of probabilistic models based on proper scoring rules,covering a wide range of situations in applied work. This paper discussesimplementation and usage details, presents case studies from meteorology andeconomics, and points to the relevant background literature.

Evaluating probabilistic forecasts with scoringRules