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On causality test for time series of counts based on poisson ingarch models with application to crime and temperature data

机译:基于Poisson Indarch模型的时间序列因果关系试验与犯罪和温度数据

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摘要

In this study, we consider the causality test for the integer-valued time series. Using the mean equation of Poisson INGARCH models, we construct a regression that includes exogenous variables. The test is then constructed based on the least squares estimator and is shown to follow a chi-square distribution under the null of no causal relationships. A simulation study and real data analysis using the crime and temperature data in Chicago are provided for illustration.
机译:在这项研究中,我们考虑了整数时间序列的因果关系测试。使用泊松Ingarch模型的均值方程,我们构建一个包括外源变量的回归。然后基于最小二乘估计器构造测试,并且被示出在没有因果关系的NULL下遵循CHI方分布。提供了使用芝加哥犯罪和温度数据的仿真研究和实际数据分析。

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