Modelling multiple time series via common factors
Modelling multiple time series via common factors
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DOI：
10.1093/biomet/asn009
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发表时间：
2008-06
期刊：
影响因子：
2.7
通讯作者：
Jiazhu Pan;Q. Yao
中科院分区：
文献类型：
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作者：
Jiazhu Pan;Q. Yao
提出了一种估计多时间序列公因子的新方法。新方法的一个显著特点是它适用于某些非平稳时间序列。通过逐步扩展白噪声空间来识别不可观测的、非平稳的因素，从而通过几个低维子问题来解决高维优化问题。研究了估计的渐近性质。用模拟数据集和真实数据集说明了所提出的方法。
We propose a new method for estimating common factors of multiple time series. One distinctive feature of the new approach is that it is applicable to some nonstationary time series. The unobservable, nonstationary factors are identified by expanding the white noise space step by step, thereby solving a high-dimensional optimization problem by several low-dimensional sub-problems. Asymptotic properties of the estimation are investigated. The proposed methodology is illustrated with both simulated and real datasets.