An integer-valued threshold autoregressive process based on negative binomial thinning

作     者：Yang, Kai Wang, Dehui Jia, Boting Li, Han 

作者机构：Jilin Univ Inst Math Changchun 130012 Jilin Peoples R China Jilin Univ Finance & Econ Sch Stat Changchun 130117 Jilin Peoples R China 

出 版 物：《STATISTICAL PAPERS》 (统计学文集)

年 卷 期：2018年第59卷第3期

页      面：1131-1160页

核心收录：

学科分类：0202[经济学-应用经济学] 02[经济学] 020208[经济学-统计学] 07[理学] 0714[理学-统计学（可授理学、经济学学位）] 

基　　金：National Natural Science Foundation of China [11271155, 11371168, J1310022, 11571138, 11501241, 11571051] Science and Technology Research Program of Education Department in Jilin Province for the 12th Five-Year Plan Jilin Province Natural Science Foundation [20130101066JC, 20130522102JH, 20150520053JH] 

主　　题：Integer-valued thresholdmodels Min-Min algorithm Negative binomial thinning Estimation 

摘      要：In this paper, we introduce an integer-valued threshold autoregressive process, which is driven by independent negative-binomial distributed random variables and based on negative binomial thinning. Basic probabilistic and statistical properties of this model are discussed. Conditional least squares and conditional maximum likelihood estimators and corresponding iterative algorithms are investigated for both the cases that the threshold variable is known or not. Also, the asymptotic properties of the estimators are obtained. Finally, some numerical results of the estimates and a real data example are presented.