ABSTRACT

To provide a more flexible model of count data, we extend the first-order integer-valued autoregressive model with serially dependent innovations based on the dependent thinning operator. This model is appropriate for modelling the number of dependent random events affecting each other when the number of new cases depend on the previous count through a linear functional relationship. Several statistical properties of the model are determined, parameters are estimated by some methods and their properties are studied via simulations. This study was carried out to investigate the efficiency of the new model by two real count data sets, the number of contagious diseases and robbery.

摘要

为了提供更灵活的计数数据模型，我们扩展了一阶整数值自回归模型，并基于依赖细化算子进行了串行依赖创新。当新病例的数量通过线性函数关系依赖于先前的计数时，该模型适用于对相互影响的依赖随机事件的数量进行建模。确定了模型的几个统计特性，通过一些方法估计了参数，并通过模拟研究了它们的特性。这项研究是通过两个真实的计数数据集，传染病和抢劫的数量来调查新模型的效率。