A Study for Missing Values in PINAR(1)T Processes
A Study for Missing Values in PINAR(1)T Processes
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DOI：
10.1080/03610926.2012.717664
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发表时间：
2014-11
期刊：
影响因子：
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通讯作者：
Boting Jia;Dehui Wang;Haixiang Zhang
中科院分区：
文献类型：
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作者：
Boting Jia;Dehui Wang;Haixiang Zhang
本文提出了在缺失数据下周期为T的一阶整数值自回归过程（PINAR（1）T）的参数估计的几种方法。利用不完全数据，我们提出了两种基于条件期望和条件似然的参数估计方法。然后研究了缺失数据的三种填补方法。这些方法的性能进行了比较，通过模拟。
In this paper, we propose several approaches to estimate the parameters of the periodic first-order integer-valued autoregressive process with period T (PINAR(1)T) in the presence of missing data. By using incomplete data, we propose two approaches that are based on the conditional expectation and conditional likelihood to estimate the parameters of interest. Then we study three kinds of imputation methods for the missing data. The performances of these approaches are compared via simulations.