Eliciting a DAG for a multivariate time series of vehicle counts in a traffic network
نویسندگان
چکیده
In this paper we elicit a directed acyclic graph (DAG) for the multivariate time series of hourly vehicle counts at the junction of three major roads in the UK. A flow diagram is introduced to give a pictorial representation of the possible vehicle routes through the network. It is shown how this flow diagram, together with a map of the network, can suggest a suitable DAG which represents the conditional independence structure across the time series. We discuss how the DAG can be used to define a linear multiregression dynamic model for the multivariate time series, so that each individual series is simply modelled by a univariate dynamic linear model.
منابع مشابه
ELICITING A DIRECTED ACYCLIC GRAPH FOR A MULTIVARIATE TIME SERIES OF VEHICLE COUNTS IN A TRAFFIC NETWORK Running heading: ELICITING A DIRECTED ACYCLIC GRAPH
The problem of modelling multivariate time series of vehicle counts in traffic networks is considered. It is proposed to use a model called the linear multiregression dynamic model (LMDM). The LMDM is a multivariate Bayesian dynamic model which uses any conditional independence and causal structure across the time series to break down the complex multivariate model into simpler univariate dynam...
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