Functional Threshold Autoregressive Model

IF 1.5 3区 数学 Q2 STATISTICS & PROBABILITY Statistica Sinica Pub Date : 2024-01-01 DOI:10.5705/ss.202022.0096
Yuanbo Li, Kun Chen, Xunze Zheng, C. Yau
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引用次数: 0

Abstract

: We propose a functional threshold autoregressive model for flexible functional time series modeling. In particular, the behavior of a function at a given time point can be described by different autoregressive mechanisms, depending on the values of a threshold variable at a past time point. Sufficient conditions for the strict stationarity and ergodicity of the functional threshold autoregressive process are investigated. We develop a novel criterion-based method simultaneously conducting dimension reduction and estimating the thresholds, autoregressive orders, and model parameters. We also establish the consistency and asymptotic distributions of the estimators of both thresholds and the underlying autoregressive models. Simulation studies and an application to U.S. Treasury zero-coupon yield rates are provided to illustrate the effectiveness and usefulness of the proposed methodology.
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功能阈值自回归模型
提出了一种用于柔性函数时间序列建模的函数阈值自回归模型。特别是,函数在给定时间点的行为可以通过不同的自回归机制来描述,这取决于阈值变量在过去时间点的值。研究了函数阈值自回归过程的严格平稳性和遍历性的充分条件。我们开发了一种新的基于准则的方法,同时进行降维和估计阈值、自回归阶数和模型参数。我们还建立了阈值和潜在的自回归模型的估计量的一致性和渐近分布。本文提供了模拟研究和美国国债零息利率的应用,以说明所提出方法的有效性和实用性。
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来源期刊
Statistica Sinica
Statistica Sinica 数学-统计学与概率论
CiteScore
2.10
自引率
0.00%
发文量
82
审稿时长
10.5 months
期刊介绍: Statistica Sinica aims to meet the needs of statisticians in a rapidly changing world. It provides a forum for the publication of innovative work of high quality in all areas of statistics, including theory, methodology and applications. The journal encourages the development and principled use of statistical methodology that is relevant for society, science and technology.
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