Edge Deletion Tests in Graphical Models for Multivariate Time Series

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dc.contributor.authorReale M
dc.contributor.authorPrice CJ
dc.contributor.authorLin S
dc.contributor.authorEllis R
dc.date.accessioned2020-08-25T20:50:30Z
dc.date.available2020-08-25T20:50:30Z
dc.date.issued2019en
dc.date.updated2020-07-09T00:29:23Z
dc.description.abstractMultivariate autoregressive moving average models can be represented as graphical models with nodes representing either the autoregressive or the moving average components and the edges representing a significant partial correlation among them. Absent edges imply a parsimonious structure of the time series models. Different strategies for testing the presence of edges are presented, assessed and compared.en
dc.identifier.citationReale M, Price CJ, Lin S, Ellis R (2019). Edge Deletion Tests in Graphical Models for Multivariate Time Series. Denver: Joint Statistical Meeting. 27/07/2019-01/08/2019. JSM Proceedings, Statistical Computing Section. Alexandria, VA: American Statistical Association. 1569-1574.en
dc.identifier.urihttps://hdl.handle.net/10092/100945
dc.language.isoen
dc.rightsAll rights reserved unless otherwise stateden
dc.rights.urihttp://hdl.handle.net/10092/17651en
dc.subjectsparsityen
dc.subjectgraphical lassoen
dc.subjectparsimonious modelsen
dc.subject.anzsrcFields of Research::49 - Mathematical sciences::4905 - Statistics::490511 - Time series and spatial modellingen
dc.titleEdge Deletion Tests in Graphical Models for Multivariate Time Seriesen
dc.typeConference Contributions - Publisheden
uc.collegeFaculty of Engineering
uc.departmentMathematics and Statistics
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