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VAR Based State-space Structures: Realization, Statistics and Spectral Analysis

机译:基于VAR的状态空间结构:实现,统计和光谱分析

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The effective representation of multivariate time-series in terms of their structural indices is faced in this study, leading to the development of a corresponding scheme that is based in the interconnection between VAR and state-space models. To this, a specific state equation that retains a state matrix identical to the companion matrix of the original VAR polynomial is realized, uncovering many "hidden" information of the initial process. In light of this realization, it is shown how closed form expressions for the Green function, the covariance generating function and the spectral density can be derived through the spectrum of the state matrix, thus allowing assessment and quantification (via the notion of dispersion analysis) of every structural mode. A Yule-Walker based estimate is also provided, which applies directly to the state equation. A structural system with two degrees of freedom and closely spaced modes serves as an application of the novel scheme, using Monte Carlo analysis.
机译:这项研究面临着多元时间序列在结构指标方面的有效表示,从而导致了基于VAR和状态空间模型之间相互联系的相应方案的发展。为此,实现了一个特定的状态方程,该方程保留了与原始VAR多项式的伴随矩阵相同的状态矩阵,从而揭示了初始过程的许多“隐藏”信息。根据这种认识,说明了如何通过状态矩阵的频谱导出格林函数,协方差生成函数和频谱密度的闭式表达式,从而可以进行评估和量化(通过色散分析的概念)每个结构模式。还提供了基于Yule-Walker的估计,该估计直接适用于状态方程。使用蒙特卡洛分析,具有两个自由度和紧密间隔模式的结构系统可作为该新方案的应用。

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