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Dependence analysis of regression models in time series

ISSN号：1009-6124
期刊名称：Journal of Systems Science and Complexity
时间：2012.12
页码：1136-1142
分类：O212.1[理学—概率论与数理统计;理学—数学] O211.61[理学—概率论与数理统计;理学—数学]
作者机构：[1]Department of Science, Shenyang University of Chemical Technology, Shenyang 110142, China, School of Statis- tics, Renmin University of China, Beijing 100872, China, [2]Department of Mathematics, Illinois State University, Normal, IL, USA, [3]Center for Applied Statistics, Renmin University of China, Beijing 100872, China
相关基金：This research was supported by the National Science Foundation of China under Grant No. 71171193, the Fundamental Research Funds for the Central Universities, and the Research Funds of Renmin University of China under Grant No. 10XNI001.
相关项目：考虑风险相依的非寿险精算模型研究

作者： Wang Xuanhe|Xu Maochao|Meng Shengwang|

中文摘要：

在这篇论文，一个线性回归模型的相对依赖被学习。特别地， autoregressive 的依赖及时当模特儿系列被调查。它与趋势和飘移模型，为一阶的非静止的 autoregressive 模型和随机的散步被看那在二个状态之间的依赖减少与落后。一些数字例子表现为很好。

英文摘要：

In this paper, the relative dependence of a linear regression model is studied. In particular, the dependence of autoregressive models in time series are investigated. It is shown that for the first-order non-stationary autoregressive model and the random walk with trend and drift model, the dependence between two states decreases with lag. Some numerical examples are presented as well.

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