COPAR-multivariate time series modeling using the copula autoregressive model
نویسندگان
چکیده
منابع مشابه
Multivariate autoregressive modeling of fMRI time series.
We propose the use of multivariate autoregressive (MAR) models of functional magnetic resonance imaging time series to make inferences about functional integration within the human brain. The method is demonstrated with synthetic and real data showing how such models are able to characterize interregional dependence. We extend linear MAR models to accommodate nonlinear interactions to model top...
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Copula-based models provide a great deal of exibility in modelling multivariate distributions, allowing the researcher to specify the models for the marginal distributions separately from the dependence structure (copula) that links them to form a joint distribution. In addition to exibility, this often also facilitates estimation of the model in stages, reducing the computational burden. Thi...
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We propose the use of Multivariate Autoregressive (MAR) models of fMRI time series to make inferences about functional integration within the human brain. The method is demonstrated with synthetic and real data showing how such models are able to characterise inter-regional dependence. We extend linear MAR models to accommodate nonlinear interactions to model top-down modulatory processes with ...
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ژورنال
عنوان ژورنال: Applied Stochastic Models in Business and Industry
سال: 2014
ISSN: 1524-1904
DOI: 10.1002/asmb.2043