Po-RCMTINAR(1)模型的矩估计
Moment Estimation of the Po-RCMTINAR(1) Model
摘要: 本文提出了一阶泊松随机系数混合算子整数值自回归时间序列模型(Po-RCMTINAR(1))。对该模型的矩和自协方差函数进行了研究，并使用Yule-Walker方法估计估计模型中的未知参数。最后，分析了一组实际数据集并与MTINAR(1)模型比较，根据MSE准则得到一阶泊松随机系数混合算子整值自回归模型(Po-RCMTINAR(1))更适合分析此数据集。
Abstract: This paper proposes a first-order random coefficient mixed thinning integer-valued autoregressive time series model (Po-RCMTINAR(1)) as the innovation sequence has a Poisson distribution. The moment and auto-covariance function of the model are studied, and the unknown parameters are estimated using the Yule-Walker method. Finally, a set of actual data sets are used to compare with the MTINAR(1) model. According to the MSE criterion, the first-order Poisson random coefficient mixed thinning integer-valued autoregressive model (Po-RCMTINAR (1)) is more suitable for analyzing this data set.
文章引用：陈瑜, 刘秀芳, 赵丽华. Po-RCMTINAR(1)模型的矩估计[J]. 应用数学进展, 2021, 10(6): 2217-2225. https://doi.org/10.12677/AAM.2021.106231

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