Abstract
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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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.
This paper was recommended for publication by Editor Shouyang WANG.
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Wang, X., Xu, M. & Meng, S. Dependence analysis of regression models in time series. J Syst Sci Complex 25, 1136–1142 (2012). https://doi.org/10.1007/s11424-012-1091-4
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DOI: https://doi.org/10.1007/s11424-012-1091-4