多变量计数时间序列建模

IF 2 Q2 ECONOMICS

Econometrics and Statistics Pub Date : 2024-07-01 DOI:10.1016/j.ecosta.2021.11.006

Konstantinos Fokianos

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引用次数: 0

摘要

本论文评述了用于分析多元计数时间序列的自回归模型。详细讨论了一个特别感兴趣的话题，即如何为计数随机变量向量选择合适的分布。重点是多元计数时间序列分析的三种主要方法：(a) 整数自回归过程，(b) 参数驱动模型和 (c) 观察驱动模型。目的是强调一些最新的方法论发展，并提出一些可能有用的研究课题。

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Multivariate Count Time Series Modelling

Autoregressive models are reviewed for the analysis of multivariate count time series. A particular topic of interest which is discussed in detail is that of the choice of a suitable distribution for a vectors of count random variables. The focus is on three main approaches taken for multivariate count time series analysis: (a) integer autoregressive processes, (b) parameter-driven models and (c) observation-driven models. The aim is to highlight some recent methodological developments and propose some potentially useful research topics.

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来源期刊

Econometrics and Statistics ECONOMICS-

CiteScore

3.10

自引率

10.50%

发文量

期刊介绍： Econometrics and Statistics is the official journal of the networks Computational and Financial Econometrics and Computational and Methodological Statistics. It publishes research papers in all aspects of econometrics and statistics and comprises of the two sections Part A: Econometrics and Part B: Statistics.