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- Publisher Website: 10.1111/j.1467-9892.2011.00753.x
- Scopus: eid_2-s2.0-84858003749
- WOS: WOS:000301114500004
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Article: Likelihood ratio tests for the structural change of an AR(p) model to a Threshold AR(p) model
Title | Likelihood ratio tests for the structural change of an AR(p) model to a Threshold AR(p) model |
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Authors | |
Keywords | Structure change Two-parameter Gaussian process Threshold AR(p) AR(p) Likelihood ratio test |
Issue Date | 2012 |
Citation | Journal of Time Series Analysis, 2012, v. 33, n. 2, p. 223-232 How to Cite? |
Abstract | This article considers the likelihood ratio (LR) test for the structural change of an AR model to a threshold AR model. Under the null hypothesis, it is shown that the LR test converges weakly to the maxima of a two-parameter vector Gaussian process. Using the approach in Chan and Tong (1990)and Chan (1991), we obtain a parameter-free limiting distribution when the errors are normal. This distribution is novel and its percentage points are tabulated via a Monte Carlo method. Simulation studies are carried out to assess the performance of the LR test in the finite sample and a real example is given. © 2011 Blackwell Publishing Ltd. |
Persistent Identifier | http://hdl.handle.net/10722/230889 |
ISSN | 2023 Impact Factor: 1.2 2023 SCImago Journal Rankings: 0.875 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Zhu, Ke | - |
dc.contributor.author | Ling, Shiqing | - |
dc.date.accessioned | 2016-09-01T06:07:04Z | - |
dc.date.available | 2016-09-01T06:07:04Z | - |
dc.date.issued | 2012 | - |
dc.identifier.citation | Journal of Time Series Analysis, 2012, v. 33, n. 2, p. 223-232 | - |
dc.identifier.issn | 0143-9782 | - |
dc.identifier.uri | http://hdl.handle.net/10722/230889 | - |
dc.description.abstract | This article considers the likelihood ratio (LR) test for the structural change of an AR model to a threshold AR model. Under the null hypothesis, it is shown that the LR test converges weakly to the maxima of a two-parameter vector Gaussian process. Using the approach in Chan and Tong (1990)and Chan (1991), we obtain a parameter-free limiting distribution when the errors are normal. This distribution is novel and its percentage points are tabulated via a Monte Carlo method. Simulation studies are carried out to assess the performance of the LR test in the finite sample and a real example is given. © 2011 Blackwell Publishing Ltd. | - |
dc.language | eng | - |
dc.relation.ispartof | Journal of Time Series Analysis | - |
dc.subject | Structure change | - |
dc.subject | Two-parameter Gaussian process | - |
dc.subject | Threshold AR(p) | - |
dc.subject | AR(p) | - |
dc.subject | Likelihood ratio test | - |
dc.title | Likelihood ratio tests for the structural change of an AR(p) model to a Threshold AR(p) model | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1111/j.1467-9892.2011.00753.x | - |
dc.identifier.scopus | eid_2-s2.0-84858003749 | - |
dc.identifier.volume | 33 | - |
dc.identifier.issue | 2 | - |
dc.identifier.spage | 223 | - |
dc.identifier.epage | 232 | - |
dc.identifier.eissn | 1467-9892 | - |
dc.identifier.isi | WOS:000301114500004 | - |
dc.identifier.issnl | 0143-9782 | - |