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Multiscale breakpoint detection in piecewise stationary AR models

Cho, Haeran and Fryzlewicz, Piotr (2008) Multiscale breakpoint detection in piecewise stationary AR models. In: IASC2008, 5-8 December 2008, Yokohama, Japan. (Unpublished)

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Abstract

In this paper, we are interested in the problem of detecting breakpoints in piecewise stationary autoregressive (AR) processes. For short time series, stationarity assumption is common. However, for longer time series, this assumption is often unrealistic. Besides, many naturally occurring phenomena cannot be modelled as stationary processes. Therefore modelling stochastic time series under nonstationary assumption is often appealing, and finnds its application in many areas, such as speech processing, biomedical signal processing, and seismology to name a few.

Item Type: Conference or Workshop Item (Paper)
Official URL: http://jasp.ism.ac.jp/~iasc2008/
Additional Information: © 2008 The authors
Library of Congress subject classification: H Social Sciences > HA Statistics
Sets: Departments > Sociology
Rights: http://www.lse.ac.uk/library/usingTheLibrary/academicSupport/OA/depositYourResearch.aspx
Date Deposited: 11 Sep 2009 11:49
URL: http://eprints.lse.ac.uk/25163/

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