First-order random coefficients integer-valued threshold autoregressive processes

被引：37

作者：

Li, Han ^{[1
]}

Yang, Kai ^{[1
]}

Zhao, Shishun ^{[1
]}

Wang, Dehui ^{[1
]}

机构：

[1] Jilin Univ, Sch Math, Changchun 130012, Jilin, Peoples R China

来源：

ASTA-ADVANCES IN STATISTICAL ANALYSIS | 2018年 / 102卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Threshold integer-valued autoregressive models; Random coefficient models; Binomial thinning; Estimation; Forecasting; D-NeSS algorithm; LEAST-SQUARES ESTIMATION; TIME-SERIES; MODELS; COUNTS; INFERENCE;

D O I：

10.1007/s10182-017-0306-3

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：

In this paper, we introduce a first-order random coefficient integer-valued threshold autoregressive process, which is based on binomial thinning. Basic probabilistic and statistical properties of this model are discussed. Conditional least squares and conditional maximum likelihood estimators are derived for both the cases that the threshold variable is known or not. The asymptotic properties of the estimators are established. Moreover, forecasting problem is addressed. Finally, some numerical results of the estimates and a real data example are presented.

引用

页码：305 / 331

页数：27

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