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
收藏
页码：442 / 458
页数：17
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