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.

引用

页码：1622 / 1644

页数：23

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