Asymptotic inference for moderate deviations from a unit root of nearly unstable INAR(1) processes

被引:1
|
作者
Liu, Congmin [1 ]
Liu, Chang [1 ]
Bai, Yansong [1 ]
Wang, Dehui [2 ]
机构
[1] Jilin Univ, Sch Math, Changchun, Peoples R China
[2] Liaoning Univ, Sch Math & Stat, Shenyang 110036, Peoples R China
基金
中国国家自然科学基金;
关键词
Asymptotic normality; INAR processes; moderate deviations; nearly unstable; TIME-SERIES; STRUCTURAL-CHANGE; POISSON; MODELS;
D O I
10.1080/00949655.2022.2134382
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The INAR(1) processes with coefficients alpha(n) = 1 - c/kn , where c > 0 is a fixed constant and {k(n)}(n is an element of N) is a deterministic sequence growing to infinity at a slower rate than n, which are often referred to as nearly unstable INAR processes with moderate deviations from a unit root. We consider some basic properties of the processes and obtain the conditional least squares estimation of the coefficient alpha(n) , which converges to a normal distribution at speed n(1/2)k(n). The simulation study provides numerical support for the theoretical results. The practical utility is illustrated in the data sets about liquor offences, claims of short-term disability and COVID-19, respectively.
引用
收藏
页码:1318 / 1336
页数:19
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