| 基于残差加权经验过程方法的自回归模型分布变点监测 |
| |
| 引用本文： | 李拂晓,田铮,陈占寿.基于残差加权经验过程方法的自回归模型分布变点监测[J].数学研究及应用,2015,35(3):330-342. |
| |
| 作者姓名： | 李拂晓 田铮 陈占寿 |
| |
| 作者单位： | 西北工业大学理学院, 陕西 西安 710129;西北工业大学理学院, 陕西 西安 710129; 中国科学院遥感应用研究所, 北京 100101;青海师范大学数学与信息科学系, 青海 西宁810008 |
| |
| 基金项目： | 国家自然科学基金 (Grant No.11301291),中科院遥感科学国家重点实验室开放课题(Grant No.OFSLRSS201206). |
| |
| 摘 要： | Change monitoring of distribution in time series models is an important issue.This paper proposes a procedure for monitoring changes in the error distribution of autoregressive time series,which is based on a weighed empirical process of residuals with weights equal to the regressors.The asymptotic properties of our monitoring statistic are derived under the null hypothesis of no change in distribution.The finite sample properties are investigated by a simulation.As it turns out,the procedure is not only able to detect distributional changes but also changes in the regression coefficient and mean.Finally,we apply the statistic to a groups of financial data.
|
| 关 键 词： | distributional changes autoregressive models weighted empirical process of residuals |
| 收稿时间： | 2013/12/10 0:00:00 |
| 修稿时间： | 3/9/2015 12:00:00 AM |
Monitoring Distributional Changes in Autoregressive Models Based on Weighted Empirical Process of Residuals |
| |
| Fuxiao LI,Zheng TIAN and Zhanshou CHEN.Monitoring Distributional Changes in Autoregressive Models Based on Weighted Empirical Process of Residuals[J].Journal of Mathematical Research with Applications,2015,35(3):330-342. |
| |
| Authors: | Fuxiao LI Zheng TIAN and Zhanshou CHEN |
| |
| Institution: | Department of Applied Mathematics, Northwestern Polytechnical University, Shaanxi 710129, P. R. China;Department of Applied Mathematics, Northwestern Polytechnical University, Shaanxi 710129, P. R. China; State Key Laboratory of Remote Sensing Science, Chinese Academy of Science, Beijing 100101, P. R. China;Department of Mathematics and information, Qinghai Normal University, Qinghai 810008, P. R. China |
| |
| Abstract: | Change monitoring of distribution in time series models is an important issue. This paper proposes a procedure for monitoring changes in the error distribution of autoregressive time series, which is based on a weighed empirical process of residuals with weights equal to the regressors. The asymptotic properties of our monitoring statistic are derived under the null hypothesis of no change in distribution. The finite sample properties are investigated by a simulation. As it turns out, the procedure is not only able to detect distributional changes but also changes in the regression coefficient and mean. Finally, we apply the statistic to a groups of financial data. |
| |
| Keywords: | distributional changes autoregressive models weighted empirical process of residuals |
| 本文献已被 CNKI 等数据库收录！ |
| 点击此处可从《数学研究及应用》浏览原始摘要信息 |
| 点击此处可从《数学研究及应用》下载免费的PDF全文 |
