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Quantifying heteroskedasticity via binary decomposition

conference contribution
posted on 2013-01-01, 00:00 authored by Marwa Hassan, Mohammed Hossny, Saeid Nahavandi, Douglas CreightonDouglas Creighton
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.

History

Event

Computer Modelling and Simulation. International Conference (15th : 2013 : Cambridge, England)

Pagination

112 - 116

Publisher

IEEE Computer Society

Location

Cambridge, England

Place of publication

Piscataway, N.J.

Start date

2013-04-10

End date

2013-04-12

ISBN-13

9780769549941

Language

eng

Publication classification

E1 Full written paper - refereed

Title of proceedings

UKSim 2013 : Proceedings of the 15th International Conference on Computer Modelling and Simulation

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