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          Institute: MPI für biologische Kybernetik     Collection: Biologische Kybernetik     Display Documents



ID: 548377.0, MPI für biologische Kybernetik / Biologische Kybernetik
Estimation of a Structural Vector Autoregression Model Using Non-Gaussianity
Authors:Hyvärinen, A.; Zhang, K.; Shimizu, S.; Hoyer, P.
Date of Publication (YYYY-MM-DD):2010-05
Title of Journal:Journal of Machine Learning Research
Volume:11
Start Page:1709
End Page:1731
Audience:Not Specified
Intended Educational Use:No
Abstract / Description:Analysis of causal effects between continuous-valued variables typically uses either autoregressive models or structural equation models with instantaneous effects. Estimation of Gaussian, linear structural equation models poses serious identifiability problems, which is why it was recently proposed to use non-Gaussian models. Here, we show how to combine the non-Gaussian instantaneous model with autoregressive models. This is effectively what is called a structural vector autoregression (SVAR) model, and thus our work contributes to the long-standing problem of how to estimate SVAR‘s. We show that such a non-Gaussian model is identifiable without prior knowledge of network structure. We propose computationally efficient methods for estimating the model, as well as methods to assess the significance of the causal influences. The model is successfully applied on financial and brain imaging data.
External Publication Status:published
Document Type:Article
Communicated by:Holger Fischer
Affiliations:MPI für biologische Kybernetik/Empirical Inference (Dept. Schölkopf)
Identifiers:LOCALID:6627
URL:http://jmlr.csail.mit.edu/papers/v11/hyvarinen10a....
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