DEPENDENCE ANALYSIS OF REGRESSION MODELS IN TIME SERIES

作     者：Xuanhe WANG Maochao XU Shengwang MENG 

作者机构：Department of ScienceShenyang University of Chemical Technology School of StatisticsRenmin University of China Department of MathematicsIllinois State University Center for Applied StatisticsRenmin University of China 

出 版 物：《Journal of Systems Science & Complexity》 (系统科学与复杂性学报（英文版）)

年 卷 期：2012年第25卷第6期

页      面：1136-1142页

核心收录：

学科分类：02[经济学] 0202[经济学-应用经济学] 020208[经济学-统计学] 07[理学] 0714[理学-统计学（可授理学、经济学学位）] 070103[理学-概率论与数理统计] 0701[理学-数学] 

基　　金：supported by the National Science Foundation of China under Grant No.71171193 the Fundamental Research Funds for the Central Universities the Research Funds of Renmin University of China under Grant No.10XNI001 

主　　题：Positive regression dependence regression model time series. 

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.