On the threshold innovation in quasi-likelihood for conditionally heteroscedastic time series
DC Field | Value | Language |
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dc.contributor.author | Yoon, Jae Eun | - |
dc.contributor.author | Hwang, Sun Young | - |
dc.date.available | 2021-02-22T05:35:17Z | - |
dc.date.issued | 2021-07 | - |
dc.identifier.issn | 0361-0918 | - |
dc.identifier.issn | 1532-4141 | - |
dc.identifier.uri | https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/2421 | - |
dc.description.abstract | This work considers conditionally heteroscedastic time series with possibly asymmetric errors (e.g., skewed t-distributions). Suppose that the error distribution is unknown and estimating functions, so called quasi-likelihood (QL) scores are employed to estimate parameters. The quasi-likelihood can be regarded as a special case of the Godambe's optimum estimating functions (see, e.g., Hwang and Basawa (2011)). To capture asymmetry in errors, a threshold-innovation is newly suggested to construct an "optimum" quasi likelihood score. It is shown that the threshold innovation is "better" than the standard innovation especially when errors are asymmetrically distributed. A simulation study is reported and a real data analysis is illustrated. | - |
dc.format.extent | 12 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | TAYLOR & FRANCIS INC | - |
dc.title | On the threshold innovation in quasi-likelihood for conditionally heteroscedastic time series | - |
dc.type | Article | - |
dc.publisher.location | 미국 | - |
dc.identifier.doi | 10.1080/03610918.2019.1593453 | - |
dc.identifier.scopusid | 2-s2.0-85064512992 | - |
dc.identifier.wosid | 000466655000001 | - |
dc.identifier.bibliographicCitation | COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, v.50, no.7, pp 2042 - 2053 | - |
dc.citation.title | COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | - |
dc.citation.volume | 50 | - |
dc.citation.number | 7 | - |
dc.citation.startPage | 2042 | - |
dc.citation.endPage | 2053 | - |
dc.type.docType | Article; Early Access | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Mathematics | - |
dc.relation.journalWebOfScienceCategory | Statistics & Probability | - |
dc.subject.keywordAuthor | ARCH | - |
dc.subject.keywordAuthor | Asymmetric errors | - |
dc.subject.keywordAuthor | Quasi-likelihood | - |
dc.subject.keywordAuthor | Threshold-innovation | - |
dc.identifier.url | https://www.tandfonline.com/doi/full/10.1080/03610918.2019.1593453 | - |
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