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吉林化工学院学报, 2023, 40(5): 62-66     https://doi.org/10.16039/j.cnki.cn22-1249.2023.05.012
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基于推广的负二项稀疏算子的随机系数INAR(1)模型及其应用
曹晓涵1,张庆春2*,赵宸稷1
1.吉林化工学院 信息与控制工程学院,吉林 吉林 132022;2.吉林化工学院 理学院,吉林 吉林 132022
A Random Coefficient INAR(1) Process based on a Generalized Negative Binomial Thinning Operator and Its Applications
CAO Xiaohan1, ZHANG Qingchun2*,ZHAO Chenji1
1.School of Information and Control Engineering, Jilin Institute of Chemical Technology, Jilin 132022, China; 2.School of Science, Jilin Institute of Chemical Technology, Jilin 132022, China
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摘要 

基于推广的负二项稀疏算子构建带有随机系数的一元INAR(1)模型,推导了该模型的概率统计性质,采用最小二乘估计法进行参数估计并进行了数值模拟。最后给出一个实例应用,并将该模型与其他模型进行对比研究,结果显示带有随机系数的基于推广的负二项稀疏算子的一元INAR(1)模型更适用于实际数据。

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曹晓涵
张庆春
赵宸稷
关键词:  推广的负二项稀疏算子  INAR(1)模型  最小二乘估计  随机系数     
Abstract: 

Based on the generalized negative binomial thinning operator, a one-dimensional INAR(1) process with random coefficients is constructed, the probabilistic statistical properties of the model are derived, parameter estimation is carried out by least squares estimation, and numerical simulations are performed. Finally, an example application is given and the model is studied in comparison with other models, and the results show that the one-dimensional INAR(1) process with random coefficients based on the generalized negative binomial thinning operator is more applicable for real data.

Key words:  Generalized negative binomial thinning operator    INAR(1) process    least squares estimation    random coefficient
               出版日期:  2023-05-25      发布日期:  2023-05-25      整期出版日期:  2023-05-25
ZTFLH:  O 212.1  
引用本文:    
曹晓涵, 张庆春, 赵宸稷. 基于推广的负二项稀疏算子的随机系数INAR(1)模型及其应用 [J]. 吉林化工学院学报, 2023, 40(5): 62-66.
CAO Xiaohan, ZHANG Qingchun, ZHAO Chenji. A Random Coefficient INAR(1) Process based on a Generalized Negative Binomial Thinning Operator and Its Applications . Journal of Jilin Institute of Chemical Technology, 2023, 40(5): 62-66.
链接本文:  
http://xuebao.jlict.edu.cn/CN/10.16039/j.cnki.cn22-1249.2023.05.012  或          http://xuebao.jlict.edu.cn/CN/Y2023/V40/I5/62
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