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Quantifying heteroskedasticity via binary decomposition

Hassan, Marwa, Hossny, Mohammed, Nahavandi, Saeid and Creighton, Douglas 2013, Quantifying heteroskedasticity via binary decomposition, in UKSim 2013 : Proceedings of the 15th International Conference on Computer Modelling and Simulation, IEEE Computer Society, Piscataway, N.J., pp. 112-116, doi: 10.1109/UKSim.2013.76.

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Title Quantifying heteroskedasticity via binary decomposition
Author(s) Hassan, Marwa
Hossny, MohammedORCID iD for Hossny, Mohammed orcid.org/0000-0002-1593-6296
Nahavandi, Saeid
Creighton, DouglasORCID iD for Creighton, Douglas orcid.org/0000-0002-9217-1231
Conference name Computer Modelling and Simulation. International Conference (15th : 2013 : Cambridge, England)
Conference location Cambridge, England
Conference dates 10-12 Apr. 2013
Title of proceedings UKSim 2013 : Proceedings of the 15th International Conference on Computer Modelling and Simulation
Editor(s) [Unknown]
Publication date 2013
Conference series Computer Modelling and Simulation International Conference
Start page 112
End page 116
Total pages 5
Publisher IEEE Computer Society
Place of publication Piscataway, N.J.
Keyword(s) quantifying heteroskedasticity
ARCH test
Summary This paper presents a quantifying measure for heteroskedasticity of a time series. In this research, heteroskedasticity levels are measured by decomposing the examined time series recursively into homoskedastic segments. Each segment of the examined time series is decomposed into smaller segments if it tests positively to heteroskedasticity tests. The final quantified value of the heteroskedasticity level is the number of homoskedastic segments. The proposed measure is robust and detects heteroskedasticity in small average variance datasets.
ISBN 9780769549941
Language eng
DOI 10.1109/UKSim.2013.76
Field of Research 100402 Medical Biotechnology Diagnostics (incl Biosensors)
Socio Economic Objective 970111 Expanding Knowledge in the Medical and Health Sciences
HERDC Research category E1 Full written paper - refereed
Persistent URL http://hdl.handle.net/10536/DRO/DU:30055218

Document type: Conference Paper
Collection: Centre for Intelligent Systems Research
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