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Graphical models for structural VARMA representations: 18th World IMACS Congress and International Congress on Modelling and Simulation: Interfacing Modelling and Simulation with Mathematical and Computational Sciences, MODSIM 2009

Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review

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Publication date17/07/2009
Number of pages6
Pages1175-1180
<mark>Original language</mark>English
Event18th World IMACS Congress and International Congress on Modelling and Simulation: Interfacing Modelling and Simulation with Mathematical and Computational Sciences, MODSIM 2009 - Cairns Convention Centre , Cairns, Australia
Duration: 13/07/2009 → 17/07/2009
Conference number: 160152

Conference

Conference18th World IMACS Congress and International Congress on Modelling and Simulation: Interfacing Modelling and Simulation with Mathematical and Computational Sciences, MODSIM 2009
Abbreviated titleMODSIM 2009
Country/TerritoryAustralia
CityCairns
Period13/07/09 → 17/07/09

Abstract

Sparse structural VAR representation can effectively be identified by using graphical modeling. In this paper we extend this approach to the the identification of sparse structural VARMA representations. We illustrate our methods with an application to a set of three monthly flour price series that has been the subject of previous approaches to structural VARMA modeling. We compare and contrast structural VARMA(1,1) and VAR(2) models for this data. © MODSIM 2009.All rights reserved.

Bibliographic note

Conference code: 160152 Export Date: 18 June 2020 Correspondence Address: Reale, M.; Department of Mathematics and Statistics, University of CanterburyNew Zealand; email: marco.reale@canterbury.ac.nz References: Akaike, H., A new look at statistical model identification (1973) IEEE Transactions on Automatic Control, AC-19, pp. 716-723; Athanasopoulos, G., Vahid, F., A complete VARMA modelling methodology based on scalar components (2008) Journal of Time Series Analysis, 29, pp. 533-554; Grubb, H., A multivariate time series analysis of some flour price data (1992) Applied Statistics, 41, p. 95107; Lauritzen, S.L., Spiegelhalter, D.J., Local computations with probabilities on graphical structures and their applications to expert systems (1988) Journal of the Royal Statistical Society B, 50, pp. 157-224; Reale, M., Tunnicliffe Wilson, G., Identification of vector AR models with recursive structural errors using conditional independence graphs (2001) Statistical Methods and Applications, 10, pp. 49-65; Spirtes, P., Glymour, C., Scheines, R., (2000) Causation, Prediction and Search, , MIT Press, Cambridge, MA; Tunnicliffe Wilson, G., Reale, M., Morton, A.S., Developments in multivariate time series modeling (2001) Estadistica, 53, pp. 353-395; Tiao, G.C., Tsay, R.S., Model specification in multivariate time series (1989) Journal of the Royal Statistical Society Series B, 51, pp. 157-213; Whittaker, J.C., (1990) Graphical Models in Applied Multivariate Statistics, , Wiley, Chichester