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dc.contributor.authorSucarrat, Genaro
dc.date.accessioned2023-09-26T12:38:07Z
dc.date.available2023-09-26T12:38:07Z
dc.date.created2022-02-16T12:45:02Z
dc.date.issued2021
dc.identifier.citationThe R Journal. 2021, 13 (1), 276-291.
dc.identifier.issn2073-4859
dc.identifier.urihttps://hdl.handle.net/11250/3092086
dc.description.abstractThe garchx package provides a user-friendly, fast, flexible, and robust framework for the estimation and inference of GARCH(p, q, r)-X models, where p is the ARCH order, q is the GARCH order, r is the asymmetry or leverage order, and ’X’ indicates that covariates can be included. Quasi Maximum Likelihood (QML) methods ensure estimates are consistent and standard errors valid, even when the standardized innovations are non-normal or dependent, or both. Zero-coefficient restrictions by omission enable parsimonious specifications, and functions to facilitate the non-standard inference associated with zero-restrictions in the null-hypothesis are provided. Finally, in the formal comparisons of precision and speed, the garchx package performs well relative to other prominent GARCH-packages on CRAN.
dc.language.isoeng
dc.titlegarchx: Flexible and Robust GARCH-X Modeling
dc.title.alternativegarchx: Flexible and Robust GARCH-X Modeling
dc.typePeer reviewed
dc.typeJournal article
dc.description.versionpublishedVersion
dc.source.pagenumber276-291
dc.source.volume13
dc.source.journalThe R Journal
dc.source.issue1
dc.identifier.doi10.32614/rj-2021-057
dc.identifier.cristin2002327
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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