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Determining the order of the functional autoregressive model

机译:确定功能自回归模型的顺序

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摘要

We propose a multistage testing procedure to determine the order p of a functional autoregressive process, FAR (p). At its core is the representation of the FAR(p) process as a fully functional linear model with dependent regressors. Estimating the kernel function in this linear model allows us to construct a test statistic which has, approximately, a chi-square distribution with the number of degrees of freedom determined by the number of functional principal components used to represent the data. The asymptotic justification relies on the concept of L~p-m-approximability which quantifies the temporal dependence of functional time series. The procedure enjoys very good finite sample properties, as confirmed by a simulation study and applications to functional time series derived from credit card transactions and Eurodollar futures data.
机译:我们提出了一个多阶段测试程序来确定功能自回归过程FAR(p)的阶数p。 FAR(p)过程的核心是具有相关回归变量的全功能线性模型。在此线性模型中估计内核函数使我们能够构建一个检验统计量,该统计量近似具有卡方分布,其自由度的数量由用来表示数据的功能主成分的数量确定。渐近证明依赖于L〜p-m-逼近性的概念,该概念量化了功能时间序列的时间依赖性。该模拟程序具有很好的有限样本属性,这已通过模拟研究证实,并应用于从信用卡交易和欧洲美元期货数据得出的功能时间序列。

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