Continuous-time locally stationary time series models

Pub Date : 2021-04-28 DOI:10.1017/apr.2022.64
Annemarie Bitter, R. Stelzer, Bennet Ströh
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引用次数: 4

Abstract

Abstract We adapt the classical definition of locally stationary processes in discrete time (see e.g. Dahlhaus, ‘Locally stationary processes’, in Time Series Analysis: Methods and Applications (2012)) to the continuous-time setting and obtain equivalent representations in the time and frequency domains. From this, a unique time-varying spectral density is derived using the Wigner–Ville spectrum. As an example, we investigate time-varying Lévy-driven state space processes, including the class of time-varying Lévy-driven CARMA processes. First, the connection between these two classes of processes is examined. Considering a sequence of time-varying Lévy-driven state space processes, we then give sufficient conditions on the coefficient functions that ensure local stationarity with respect to the given definition.
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连续时间局部平稳时间序列模型
摘要我们将离散时间中局部平稳过程的经典定义(参见Dahlhaus,“局部平稳过程”,在时间序列分析:方法和应用(2012)中)应用于连续时间设置,并获得时域和频域中的等效表示。由此,使用Wigner–Ville谱导出了一个独特的时变谱密度。作为一个例子,我们研究了时变Lévy驱动的状态空间过程,包括一类时变Lèvy驱动CARMA过程。首先,研究了这两类过程之间的联系。考虑一系列时变Lévy驱动的状态空间过程,我们给出了系数函数的充分条件,以确保相对于给定定义的局部平稳性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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