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

被引：4

作者：

Lee, Youngmi ^{[1
]}

Lee, Sangyeol ^{[1
]}

机构：

[1] Seoul Natl Univ, Dept Stat, Seoul 08826, South Korea

来源：

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 2019年 / 48卷 / 06期

基金：

新加坡国家研究基金会;

关键词：

Causality test; Time series of counts; Poisson INGARCH model; PARAMETER CHANGE TEST;

D O I：

10.1080/03610918.2018.1429618

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

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.

引用

页码：1901 / 1911

页数：11

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