Estimation and testing for the integer-valued threshold autoregressive models based on negative binomial thinning

被引：13
|
作者：
Wang, Xiaohong [1 ,2 ]
Wang, Dehui [1 ]
Yang, Kai [3 ]
Xu, Da [1 ]
机构：
[1] Jilin Univ, Sch Math, Changchun, Jilin, Peoples R China
[2] Jilin Normal Univ, Coll Math, Siping, Jilin, Peoples R China
[3] Changchun Univ Technol, Sch Math & Stat, Changchun 130012, Jilin, Peoples R China
来源：
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 2021年 / 50卷 / 06期
基金：
中国国家自然科学基金;
关键词：
Threshold autoregressive processes; Change point autoregressive processes; Negative binomial thinning; Empirical likelihood; Nonlinearity test; EMPIRICAL LIKELIHOOD; TIME-SERIES; COUNTS;
D O I：
10.1080/03610918.2019.1586929
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：
To better describe the characteristics of time series of counts such as overdispersion or structural change, in this paper, we redefines the integer-valued threshold autoregressive models based on negative binomial thinning (NBTINAR(1)) under a weaker condition that the expectation of the innovations is finite. Parameters' point estimation and interval estimation problems are considered. A method to test the nonlinearity of the data is provided. As an illustration, we conduct a simulation study and empirical analysis of Pittsburgh crime data sets.
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页码：1622 / 1644
页数：23
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