用scoringRules评估概率预测
Evaluating probabilistic forecasts with scoringRules
摘要：
对未来事件的概率分布形式的概率预报在包括气象学、水文学、经济学和人口学在内的几个领域已经变得流行。在典型的应用中，可以使用许多替代的统计模型和数据源来产生概率预测。因此，评价和选择竞争的方法是一项重要的任务。R的scoringRules包提供了基于适当的评分规则对概率模型进行比较评估的功能，涵盖了应用工作中的各种情况。本文讨论了实现和使用的细节，从气象学和经济学的案例研究，并指出相关的背景文献。
英文摘要：
Probabilistic forecasts in the form of probability distributions over future events have become popular in several fields including meteorology, hydrology, economics, and demography. 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. This paper discusses implementation and usage details, presents case studies from meteorology and economics, and points to the relevant background literature.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
