Analyzing associations in multivariate binary time series
Loading...
Date
2006-03-16T14:35:47Z
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
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 nonĀ-causalities since they correspond to zero parameter values.
Description
Table of contents
Keywords
Canonical interaction, Granger non-causalities, Mixed parameterization, Zero parameter values