存在一个周期性和季节性的 INAR 进程

IF 1.2 4区 数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Journal of Time Series Analysis Pub Date : 2024-05-13 DOI:10.1111/jtsa.12746
Márton Ispány, Pascal Bondon, Valdério Anselmo Reisen, Paulo Roberto Prezotti Filho
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引用次数: 0

摘要

针对周期性相关和季节性非负整数值自回归过程的存在性和唯一性,给出了涉及模型参数的谱准则。利用隐式状态空间表示法推导出了该模型周期性静态分布的均值和协方差函数结构。为该过程建立了两种无穷级数表示法,即移动平均表示法和移民生成表示法。在后一种表示法的基础上,提出了一种新颖的可并行模拟方法来生成过程。
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Existence of a Periodic and Seasonal INAR Process

A spectral criterion involving the model parameters is given for the existence and uniqueness of a periodically correlated and seasonal non-negative integer-valued autoregressive process. The structure of the mean and covariance functions of the periodically stationary distribution of the model is derived using its implicit state-space representation. Two infinite series representations for the process, the moving average, and the immigrant generation, are established. Based on the latter representation, a novel and parallelizable simulation method is proposed to generate the process.

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来源期刊
Journal of Time Series Analysis
Journal of Time Series Analysis 数学-数学跨学科应用
CiteScore
2.00
自引率
0.00%
发文量
39
审稿时长
6-12 weeks
期刊介绍: During the last 30 years Time Series Analysis has become one of the most important and widely used branches of Mathematical Statistics. Its fields of application range from neurophysiology to astrophysics and it covers such well-known areas as economic forecasting, study of biological data, control systems, signal processing and communications and vibrations engineering. The Journal of Time Series Analysis started in 1980, has since become the leading journal in its field, publishing papers on both fundamental theory and applications, as well as review papers dealing with recent advances in major areas of the subject and short communications on theoretical developments. The editorial board consists of many of the world''s leading experts in Time Series Analysis.
期刊最新文献
Issue Information Editorial Announcement: Journal of Time Series Analysis Distinguished Authors 2024 Time Series for QFFE: Special Issue of the Journal of Time Series Analysis High-Frequency Instruments and Identification-Robust Inference for Stochastic Volatility Models Issue Information
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