Generalized likelihood ratio approach for identifying nonlinear structural vector autoregressive causal graphs
WEI Yue-song
School of Mathematical Science, Huaibei Normal University, Huaibei 235000, China
Department of Applied Mathematics, Northwest Polytechnical University, Xi’an 710129, China
Abstract In this paper, the causal relationships among variables of nonlinear structure vector autoregressive model are studied using graphical model method. The nonlinear structure vector autoregressive causal graph is presented, and a generalized likelihood ratio approach is developed to infer the causal relationships. The generalized likelihood ratio statistics of contemporaneous and lagged are presented respectively, and a bootstrap method is considered for determining the null distribution of the test statistic. The validity of the proposed method is confirmed by simulations analysis.
WEI Yue-song. Generalized likelihood ratio approach for identifying nonlinear structural vector autoregressive causal graphs. Applied Mathematics A Journal of Chinese Universities, 2016, 31(2): 143-152.
