An empirical-likelihood-based structural-change test for INAR processes

被引：5

作者：

Yu, Kaizhi ^{[1
]}

Wang, Huiqiao ^{[1
]}

Weiss, Christian H. ^{[2
]}

机构：

[1] Southwestern Univ Finance & Econ, Dept Stat, Chengdu, Peoples R China

[2] Helmut Schmidt Univ, Dept Math & Stat, POB 700822, D-22008 Hamburg, Germany

来源：

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION | 2023年 / 93卷 / 03期

关键词：

Count time series; COVID-19; empirical likelihood; INAR model; parameter change test; TIME-SERIES; INFERENCE; MODEL;

D O I：

10.1080/00949655.2022.2109635

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The empirical likelihood ratio (ELR) test is proposed for uncovering a structural change in integer-valued autoregressive (INAR) processes. The limiting distribution is derived under the null hypothesis that the parameter did not change at the anticipated change points. To evaluate the finite-sample performance of the proposed ELR test, the empirical sizes and powers are investigated in a simulation study. The ELR test is also applied to real data on infectious disease and crime counts.

引用

页码：442 / 458

页数：17

共 47 条

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