研究人员推出了FoReco和FoRecoML，这是一个为R设计的统一工具箱，旨在增强预测协调。这些包解决了时间序列数据的横截面、时间段和跨时间段协调缺乏全面软件的问题。FoReco实现了经典和基于回归的线性方法，而FoRecoML提供了非线性机器学习方法，可满足新手和专家用户的需求。 AI
影响 提供了使用经典和机器学习方法提高时间序列预测准确性和一致性的新工具。
排序理由 该集群描述了用于预测协调的新R包的发布，该发布在arXiv预印本中有详细介绍。
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arXiv:2604.27696v1 Announce Type: cross Abstract: Forecast reconciliation has become key to improving the accuracy and coherence of forecasts for linearly constrained multiple time series, such as hierarchical and grouped series. Yet, comprehensive software that jointly covers cr…
Forecast reconciliation has become key to improving the accuracy and coherence of forecasts for linearly constrained multiple time series, such as hierarchical and grouped series. Yet, comprehensive software that jointly covers cross-sectional, temporal, and cross-temporal reconc…