Analyzing Associations in Multivariate Binary Time Series
We analyze multivariate binary time series using a mixed parameterization in terms of the conditional expectations given the past and the pairwise canonical interactions among contemporaneous variables. This allows consistent inference on the influence of past variables even if the contemporaneous associations are misspecified. Particularly, we can detect and test Granger non-causalities since they correspond to zero parameter values.
Year of publication: |
2006
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Authors: | Fried, Roland ; Kuhls, Silvia ; Molina, Isabel |
Institutions: | Institut für Wirtschafts- und Sozialstatistik, Universität Dortmund |
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freely available
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