DocumentCode :
535238
Title :
Identification of structural vector autoregrssive model based on time series chain graphs
Author :
Wei, Yuesong ; Tian, Zheng ; Chen, Zhanshou ; Leng, Chengcai
Author_Institution :
Dept. of Appl. Math., Northwestern Polytech. Univ., Xi´´an, China
Volume :
7
fYear :
2010
fDate :
16-18 Oct. 2010
Firstpage :
3423
Lastpage :
3427
Abstract :
In this paper, structural vector autoregressive model is expressed as time series chain graphs. We show the equivalence between the edge of the chain graph and the corresponding coefficient of the structural VAR, and discuss the links between partial covariance among residuals and partial covariance among contemporaneous components in a VAR model. A statistic based on local density estimator is proposed to test the conditional independence and a bootstrap approach is used to determine the null distribution of the test statistic. Simulations confirm the validity of the proposed method.
Keywords :
autoregressive processes; graph theory; time series; vectors; bootstrap approach; null distribution; statistic based on local density estimator; structural vector autoregressive model; time series chain graphs; Biological system modeling; Correlation; Covariance matrix; Equations; Graphical models; Mathematical model; Time series analysis; bootstrap method; chain graphs; conditional independence; nonparametric test; structural vector autoregressive model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Signal Processing (CISP), 2010 3rd International Congress on
Conference_Location :
Yantai
Print_ISBN :
978-1-4244-6513-2
Type :
conf
DOI :
10.1109/CISP.2010.5647392
Filename :
5647392
Link To Document :
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