Monitoring Distributional Changes in Autoregressive Models Based on Weighted Empirical Process of Residuals  

作　　者：Fuxiao LI Zheng TIAN Zhanshou CHEN 

机构地区：[1]Department of Applied Mathematics,Northwestern Polytechnical University [2]State Key Laboratory of Remote Sensing Science,Chinese Academy of Science [3]Department of Mathematics and information,Qinghai Normal University

出　　处：《Journal of Mathematical Research with Applications》2015年第3期330-342,共13页数学研究及应用（英文版）

基　　金：Supported by the National Natural Science Foundation of China(Grant No.11301291);the Open Fund of State Key Laboratory of Remote Sensing Science of China(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.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 

分 类 号：O212.1[理学—概率论与数理统计]