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https://ah.lib.nccu.edu.tw/handle/140.119/66133
題名: | Extracting Informative Variables in the Validation of Two-group Causal Relationship | 作者: | 洪英超 Hung, Ying-chao; Tseng, Neng-fang |
貢獻者: | 統計系 | 關鍵詞: | Causal relationship;Vector autoregression model;Informative variables;Modified Wald test;Automatic computer-search algorithm | 日期: | 2013 | 上傳時間: | 21-May-2014 | 摘要: | The validation of causal relationship between two groups of multivariate time series data often requires the precedence knowledge of all variables. However, in practice one finds that some variables may be negligible in describing the underlying causal structure. In this article we provide an explicit definition of \"non-informative variables\" in a two-group causal relationship and introduce various automatic computer-search algorithms that can be utilized to extract informative variables based on a hypothesis testing procedure. The result allows us to represent a simplified causal relationship by using minimum possible information on two groups of variables | 關聯: | Computational Statistics, 28(3), 1151-1167 | 資料類型: | article | DOI: | http://dx.doi.org/10.1007/s00180-012-0351-z |
Appears in Collections: | 期刊論文 |
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