Analyzing associations in multivariate binary time series

Loading...
Thumbnail Image

Date

2006-03-16T14:35:47Z

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

Citation