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Generation of time series models with given spectral properties

机译:具有给定频谱特性的时间序列模型的生成

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摘要

We give a method for generation of periodically correlated and multivariate ARIMA models whose dynamic characteristics are partially or fully specified in terms of spectral poles and zeroes or their equivalents in the form of eigenvalues/eigenvectors of associated model matrices. Our method is based on the spectral decomposition of multi-companion matrices and their factorization into products of companion matrices. Generated models are needed in simulation but may also be used in estimation, e.g. to set sensible initial values of parameters for nonlinear optimization.rnWe are not aware of any other general method for multivariate linear systems of comparable generality and control over the spectral properties of the generated model.
机译:我们提供了一种生成周期性相关和多元ARIMA模型的方法,该模型的动态特征部分或全部以频谱极点和零或它们的等价形式以关联模型矩阵的特征值/特征向量的形式指定。我们的方法是基于多伴随矩阵的频谱分解及其分解为伴随矩阵的乘积。仿真中需要生成的模型,但也可以将其用于估计,例如为合理的参数设置非线性优化的初始值。我们不知道有其他通用方法可用于具有相当通用性的多变量线性系统,并可以控制生成模型的光谱特性。

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