- Bayesian Anal.
- Volume 6, Number 2 (2011), 279-305.
Dynamic staged trees for discrete multivariate time series: forecasting, model selection and causal analysis
A new tree-based graphical model --- the dynamic staged tree --- is proposed for modelling discrete-valued discrete-time multivariate processes which are hypothesised to exhibit symmetries in how some intermediate situations might unfold. We define and implement a one-step-ahead prediction algorithm with the model using multi-process modelling and the power steady model that is robust to short-term variations in the data yet sensitive to underlying system changes. We demonstrate that the whole analysis can be performed in a conjugate way so that the potentially vast model space can be traversed quickly and then results communicated transparently. We also demonstrate how to analyse a general set of causal hypotheses on this model class. Our techniques are illustrated using a simple educational example.
Bayesian Anal., Volume 6, Number 2 (2011), 279-305.
First available in Project Euclid: 13 June 2012
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Digital Object Identifier
Mathematical Reviews number (MathSciNet)
Zentralblatt MATH identifier
Primary: 62M10: Time series, auto-correlation, regression, etc. [See also 91B84]
Secondary: 05C90: Applications [See also 68R10, 81Q30, 81T15, 82B20, 82C20, 90C35, 92E10, 94C15] 62-09: Graphical methods 62F15: Bayesian inference 62P99: None of the above, but in this section 68T30: Knowledge representation
Freeman, Guy; Smith, Jim Q. Dynamic staged trees for discrete multivariate time series: forecasting, model selection and causal analysis. Bayesian Anal. 6 (2011), no. 2, 279--305. doi:10.1214/11-BA610. https://projecteuclid.org/euclid.ba/1339612047