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高校应用数学学报
高校应用数学学报  2016, Vol. 31 Issue (2): 143-152    
    
非线性结构向量自回归因果图的广义似然比辨识方法
魏岳嵩
淮北师范大学 数学科学学院, 安徽淮北 235000
西北工业大学 应用数学系, 陕西西安 710072
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
 全文: PDF 
摘要： 利用图模型方法研究非线性结构向量自回归模型的因果性问题. 构建了非线性结构向量自回归因果图模型, 提出图模型因果性的广义似然比辨识方法. 构造同期因果关系和滞后因果关系的广义似然比统计量, 使用bootstrap方法来确定检验统计量的原分布, 模拟研究论述了方法的有效性.
关键词： 非线性结构向量自回归模型;  因果图;  条件独立;  广义似然比;  bootstrap方法    
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.
Key words: nonlinear structural vector autoregressive models    graphical models    conditional independence    generalized likelihood ratio    bootstrap method
收稿日期: 2015-01-28 出版日期: 2018-05-17
CLC:  O211.6  
基金资助: 国家自然科学基金(60375003; 61201323); 安徽省高校自然科学研究项目(KJ2015A035)
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引用本文:

魏岳嵩. 非线性结构向量自回归因果图的广义似然比辨识方法[J]. 高校应用数学学报, 2016, 31(2): 143-152.

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.

链接本文:

http://www.zjujournals.com/amjcua/CN/    或    http://www.zjujournals.com/amjcua/CN/Y2016/V31/I2/143

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