Stefanos Kechagias , Vladas Pipiras , Pavlos Zoubouloglou
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引用次数: 0
摘要
通过对某些双变量长期记忆时间序列进行随机调制,引入了一种新的一般周期性长期记忆模型。这种构造本质上分离了周期性长期记忆的两个关键特征:准周期性和长期持续性。它还允许在周期性长记忆时间序列中出现一般的周期阶段。本文讨论了合适的双变量长记忆序列的几种选择,包括参数分数积分向量 ARMA 模型。本研究中介绍的参数模型具有明确的自协方差函数,可随时用于模拟、估计和其他任务。
Cyclical long memory: Decoupling, modulation, and modeling
A new model for general cyclical long memory is introduced, by means of random modulation of certain bivariate long memory time series. This construction essentially decouples the two key features of cyclical long memory: quasi-periodicity and long-term persistence. It further allows for a general cyclical phase in cyclical long memory time series. Several choices for suitable bivariate long memory series are discussed, including a parametric fractionally integrated vector ARMA model. The parametric models introduced in this work have explicit autocovariance functions that can be readily used in simulation, estimation, and other tasks.
期刊介绍:
Stochastic Processes and their Applications publishes papers on the theory and applications of stochastic processes. It is concerned with concepts and techniques, and is oriented towards a broad spectrum of mathematical, scientific and engineering interests.
Characterization, structural properties, inference and control of stochastic processes are covered. The journal is exacting and scholarly in its standards. Every effort is made to promote innovation, vitality, and communication between disciplines. All papers are refereed.