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A robust Cusum test for SETAR-type nonlinearity in time series

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Author Info
Joseph D. Petruccelli (Department of Mathematical Sciences, Worcester Polytechnic Institute, Worcester, Massachusetts, USA)
Alina Onofrei (Division of Preventive and Behavioral Medicine, University of Massachusetts Medical School, Worcester, Massachusetts, USA)
Jayson D. Wilbur (Instrumentation Laboratory, Lexington, Massachusetts, 02421, USA)
Abstract

As a part of an effective self-exciting threshold autoregressive (SETAR) modeling methodology, it is important to identify processes exhibiting SETAR-type nonlinearity. A number of tests of nonlinearity have been developed in the literature. However, it has recently been shown that all these tests perform poorly for SETAR-type nonlinearity detection in the presence of additive outliers. In this paper, we develop an improved test for SETAR-type nonlinearity in time series. The test is an outlier-robust test based on the cumulative sums of ordered weighted residuals from generalized maximum likelihood fits. A Monte Carlo study confirms that the proposed test is competitive with existing tests for data from uncontaminated SETAR models and superior to them for SETAR data contaminated with additive outliers. Copyright © 2008 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/for.1113
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Publisher Info
Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 28 (2009)
Issue (Month): 3 ()
Pages: 266-276
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:jof:jforec:v:28:y:2009:i:3:p:266-276

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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This page was last updated on 2009-12-10.

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