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

Oxley, L. and Reale, M. and Tunnicliffe Wilson, G. (2009) 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. In: 18th World IMACS Congress and International Congress on Modelling and Simulation: Interfacing Modelling and Simulation with Mathematical and Computational Sciences, MODSIM 2009, 2009-07-132009-07-17, Cairns Convention Centre.

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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.

Item Type:

Contribution to Conference (Paper)

Journal or Publication Title:

18th World IMACS Congress and International Congress on Modelling and Simulation: Interfacing Modelling and Simulation with Mathematical and Computational Sciences, MODSIM 2009

Additional Information:

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

Subjects:

?? CONDITIONAL INDEPENDENCEMORALIZATIONMULTIVARIATE TIME SERIESVALUE ENGINEERINGGRAPHICAL MODELGRAPHIC METHODS ??

Departments:

Faculty of Science and Technology > Mathematics and Statistics

ID Code:

144858

Deposited By:

ep_importer_pure

Deposited On:

09 Jun 2021 19:20

Refereed?:

Yes

Published?:

Published

Last Modified:

17 Sep 2023 04:22

URI:

https://eprints-dev.lancs.ac.uk/id/eprint/144858