Modeling and inferences for bounded multivariate time series of counts

IF 0.6 4区 数学 Q4 STATISTICS & PROBABILITY
Sangyeol Lee, Minyoung Jo
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引用次数: 0

Abstract

This paper considers modeling bounded multivariate time series of counts and the inferential procedures of this model. For modeling, we introduce a hybrid type model similar to the scheme of integer-valued autoregressive (INAR) and conditional autoregressive heteroscedastic (INARCH) models. To estimate the model parameters, we use the conditional least squares estimator (CLSE) and minimum density power divergence estimator (MDPDE). To evaluate the small sample performances of the proposed estimators, we conduct a Monte Carlo simulation study and demonstrate that the proposed methods work well. Real data analysis is also carried out using syphilis data in the U.S. for illustration.

Abstract Image

有界多元计数时间序列的建模和推论
本文探讨了有界多变量计数时间序列的建模以及该模型的推理过程。在建模时,我们引入了一种混合型模型,类似于整值自回归(INAR)和条件自回归异速(INARCH)模型的方案。为了估计模型参数,我们使用了条件最小二乘估计器(CLSE)和最小密度功率发散估计器(MDPDE)。为了评估所提出的估计器的小样本性能,我们进行了蒙特卡罗模拟研究,并证明所提出的方法运行良好。我们还利用美国的梅毒数据进行了真实数据分析,以资说明。
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来源期刊
Journal of the Korean Statistical Society
Journal of the Korean Statistical Society 数学-统计学与概率论
CiteScore
1.30
自引率
0.00%
发文量
37
审稿时长
3 months
期刊介绍: The Journal of the Korean Statistical Society publishes research articles that make original contributions to the theory and methodology of statistics and probability. It also welcomes papers on innovative applications of statistical methodology, as well as papers that give an overview of current topic of statistical research with judgements about promising directions for future work. The journal welcomes contributions from all countries.
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