This paper deals with simultaneous prediction for time series models. In particular, it presents a simple procedure which gives well-calibrated simultaneous prediction intervals with coverage probability close to the target nominal value. Although the exact computation of the proposed intervals is usually not feasible, an approximation can be easily attained by means of a suitable bootstrap simulation procedure. This new predictive solution is much simpler to compute than those ones already proposed in the literature, based on asymptotic calculations. Applications of the bootstrap calibrated procedure to AR, MA and ARCH models are presented.

中文翻译：

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关于时间序列的同时校准预测间隔的注释

本文涉及时间序列模型的同步预测。特别是，它提供了一个简单的过程，该过程可提供经过良好校准的同时预测间隔，且覆盖概率接近目标标称值。尽管通常无法对建议的间隔进行精确计算，但是可以通过适当的引导程序仿真程序轻松获得近似值。这种新的预测解决方案比基于渐进计算的文献中已经提出的解决方案更容易计算。介绍了自举校准程序在AR，MA和ARCH模型中的应用。