This paper proposes an extension of principal component analysis to non-stationary multivariate time series data. A criterion for determining the number of final retained components is proposed. An advance correlation matrix is developed to evaluate dynamic relationships among the chosen components. The theoretical properties of the proposed method are given. Many simulation experiments show our approach performs well on both stationary and non-stationary data. Real data examples are also presented as illustrations. We develop four packages using the statistical software R that contain the needed functions to obtain and assess the results of the proposed method.

中文翻译：

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非平稳多元时间序列的移动动态主成分分析

本文提出将主成分分析扩展到非平稳多元时间序列数据。提出了确定最终保留成分数量的标准。开发了高级相关矩阵，以评估所选组件之间的动态关系。给出了所提方法的理论性质。许多仿真实验表明，我们的方法在固定数据和非固定数据上均表现良好。实际数据示例也作为示例提供。我们使用统计软件R开发了四个程序包，其中包含获得和评估所提出方法的结果所需的功能。