Evaluating probabilistic forecasts with scoringRules

28. June 2021

Comparing predictive performance

Forecasts are generally surrounded by uncertainty and being able to quantify this uncertainty is key to good decision making. Accordingly, probabilistic forecasts in the form of predictive probability distributions over future quantities or events have become popular over the last decades in various fields including meteorology, climate science, hydrology, seismology, economics, finance, demography, and political science.

In typical applications, many alternative statistical models and data sources can be used to produce probabilistic forecasts. Hence, evaluating and selecting among competing methods is an important task. The scoringRules package for R provides functionality for comparative evaluation of probabilistic models based on proper scoring rules, covering a wide range of situations in applied work.

The scoringRules package aims to be a comprehensive library for computing scoring rules. We offer implementations of several known (but not routinely applied) formulas and implement some closed-form expressions that were previously unavailable. Whenever more than one implementation variant exists, we offer statistically principled default choices. The package contains the continuous ranked probability score (CRPS) and the logarithmic score, as well as the multivariate energy score and variogram score. All of these scoring rules are proper, which means that forecasters have an incentive to state their true belief.

scoringRules was developed in the Computational Statistics group at HITS is available on CRAN, and developed on GitHub.


Alexander Jordan, Fabian Krüger, Sebastian Lerch
Evaluating Probabilistic Forecasts with scoringRules
J. Stat. Softw. (2019) 90(12):1–37, DOI: 10.18637/jss.v090.i12

About HITS

The Heidelberg Institute for Theoretical Studies (HITS) was established in 2010 by the physicist and SAP co-founder Klaus Tschira (1940-2015) and the Klaus Tschira Foundation as a private, non-profit research institute. HITS conducts basic research in the natural sciences, mathematics and computer science, with a focus on the processing, structuring, and analyzing of large amounts of complex data and the development of computational methods and software. The research fields range from molecular biology to astrophysics. The shareholders of HITS are the HITS-Stiftung, which is a subsidiary of the Klaus Tschira Foundation, Heidelberg University and the Karlsruhe Institute of Technology (KIT). HITS also cooperates with other universities and research institutes and with industrial partners. The base funding of HITS is provided by the HITS Stiftung with funds received from the Klaus Tschira Foundation. The primary external funding agencies are the Federal Ministry of Education and Research (BMBF), the German Research Foundation (DFG), and the European Union.

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