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Article: Diagnostic check for heavy tail in linear time series
| Title | Diagnostic check for heavy tail in linear time series |
|---|---|
| Authors | |
| Keywords | Autoregressive moving-average model Change point Extreme value index Peaks-over-threshold Residual |
| Issue Date | 1-Jan-2015 |
| Publisher | Elsevier |
| Citation | Statistical Methodology, 2015, v. 24, p. 1-11 How to Cite? |
| Abstract | Justification of heavy tail is an important open problem. A systematic approach is proposed to verify heavy tail in linear time series. It consists of three parts, each of which is guided by statistical tests. The analysis is supplemented by an application to ozone concentration. The methodology has the advantage that the threshold selection is data-driven. Simulations show that test results are accurate even under model misspecification. The power is good under two heavy-tailed alternatives. The test is invariant when the time series clusters at extreme level in the study of the max-autoregressive process. It also gives a preliminary measure of tail heaviness if the underlying process is heavy-tailed. |
| Persistent Identifier | http://hdl.handle.net/10722/369468 |
| ISSN | 2016 Impact Factor: 0.670 2019 SCImago Journal Rankings: 0.579 |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Wong, Siu Tung | - |
| dc.date.accessioned | 2026-01-24T00:35:22Z | - |
| dc.date.available | 2026-01-24T00:35:22Z | - |
| dc.date.issued | 2015-01-01 | - |
| dc.identifier.citation | Statistical Methodology, 2015, v. 24, p. 1-11 | - |
| dc.identifier.issn | 1572-3127 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/369468 | - |
| dc.description.abstract | <p>Justification of heavy tail is an important open problem. A systematic approach is proposed to verify heavy tail in linear time series. It consists of three parts, each of which is guided by statistical tests. The analysis is supplemented by an application to ozone concentration. The methodology has the advantage that the threshold selection is data-driven. Simulations show that test results are accurate even under model misspecification. The power is good under two heavy-tailed alternatives. The test is invariant when the time series clusters at extreme level in the study of the max-autoregressive process. It also gives a preliminary measure of tail heaviness if the underlying process is heavy-tailed.</p> | - |
| dc.language | eng | - |
| dc.publisher | Elsevier | - |
| dc.relation.ispartof | Statistical Methodology | - |
| dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
| dc.subject | Autoregressive moving-average model | - |
| dc.subject | Change point | - |
| dc.subject | Extreme value index | - |
| dc.subject | Peaks-over-threshold | - |
| dc.subject | Residual | - |
| dc.title | Diagnostic check for heavy tail in linear time series | - |
| dc.type | Article | - |
| dc.identifier.doi | 10.1016/j.stamet.2014.11.001 | - |
| dc.identifier.scopus | eid_2-s2.0-84953837691 | - |
| dc.identifier.volume | 24 | - |
| dc.identifier.spage | 1 | - |
| dc.identifier.epage | 11 | - |
| dc.identifier.issnl | 1572-3127 | - |
