...
首页> 外文期刊>Communications in Statistics >On causality test for time series of counts based on poisson ingarch models with application to crime and temperature data
【24h】

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 ingarch模型的计数时间序列因果关系检验及其在犯罪和温度数据中的应用

获取原文
获取原文并翻译 | 示例
           

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,我们考虑了整数值时间序列的因果关系检验。使用Poisson INGARCH模型的均值方程,我们构建了包含外生变量的回归。然后根据最小二乘估计量构造检验,并证明在没有因果关系的零值下遵循卡方分布。为了说明,提供了使用芝加哥犯罪和温度数据的模拟研究和真实数据分析。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号