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.
|Date of creation:||2006|
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- Kauermann G. & Carroll R.J., 2001. "A Note on the Efficiency of Sandwich Covariance Matrix Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1387-1396, December.
- Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
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