论文标题
选择人造折刀的时间序列超标剂
Selecting time-series hyperparameters with the artificial jackknife
论文作者
论文摘要
本文提出了对删除的概括-D $ JackNife，以解决时间序列的超参数选择问题。我称其为人造删除-U $ D $ Jackknife，以强调这种方法用虚拟删除代替经典的删除步骤，其中观察到的数据点被人工缺失值替换。此过程使数据顺序保持完整，并允许与时间序列兼容。该手稿证明了这种方法渐近地使用了这种方法，并通过模拟研究显示了其有限样本的优势。此外，本文通过调节外汇率的预测模型来描述其现实世界中的优势。
This article proposes a generalisation of the delete-$d$ jackknife to solve hyperparameter selection problems for time series. I call it artificial delete-$d$ jackknife to stress that this approach substitutes the classic removal step with a fictitious deletion, wherein observed datapoints are replaced with artificial missing values. This procedure keeps the data order intact and allows plain compatibility with time series. This manuscript justifies the use of this approach asymptotically and shows its finite-sample advantages through simulation studies. Besides, this article describes its real-world advantages by regulating forecasting models for foreign exchange rates.
