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dc.contributor.authorYan, Yuan
dc.contributor.authorGenton, Marc G.
dc.date.accessioned2019-03-28T11:56:06Z
dc.date.available2017-12-28T07:32:15Z
dc.date.available2019-03-28T11:56:06Z
dc.date.issued2018-05-23
dc.identifier.citationYan Y, Genton MG (2018) Non-Gaussian autoregressive processes with Tukey g-and-h transformations. Environmetrics 30: e2503. Available: http://dx.doi.org/10.1002/env.2503.
dc.identifier.issn1180-4009
dc.identifier.doi10.1002/env.2503
dc.identifier.urihttp://hdl.handle.net/10754/626528
dc.description.abstractWhen performing a time series analysis of continuous data, for example, from climate or environmental problems, the assumption that the process is Gaussian is often violated. Therefore, we introduce two non-Gaussian autoregressive time series models that are able to fit skewed and heavy-tailed time series data. Our two models are based on the Tukey (Formula presented.) -and-h transformation. We discuss parameter estimation, order selection, and forecasting procedures for our models and examine their performances in a simulation study. We demonstrate the usefulness of our models by applying them to two sets of wind speed data.
dc.description.sponsorshipThis publication is based upon the work supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Grant OSR-2015-CRG4-2640.
dc.publisherWiley
dc.relation.urlhttps://onlinelibrary.wiley.com/doi/full/10.1002/env.2503
dc.rightsArchived with thanks to Environmetrics
dc.subjectautoregressive
dc.subjectheavy tails
dc.subjectnon-Gaussian
dc.subjectskewness
dc.subjecttime series
dc.subjectTukey g-and-h transformation
dc.titleNon-Gaussian autoregressive processes with Tukey g-and-h transformations
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentStatistics Program
dc.identifier.journalEnvironmetrics
dc.eprint.versionPost-print
dc.identifier.arxivid1711.07516
kaust.personYan, Yuan
kaust.personGenton, Marc G.
kaust.grant.numberOSR-2015-CRG4-2640
dc.relation.issupplementedbyDOI:10.6084/m9.figshare.c.4075553.v1
refterms.dateFOA2018-06-13T17:11:33Z
display.relations<b>Is Supplemented By:</b><br/> <ul><li><i>[Dataset]</i> <br/> Yan, Y., Genton, M. G., &amp; Admin, W. (2018). <i>Dataset for: Non-Gaussian Autoregressive Processes with Tukey g-and-h Transformations</i>. Figshare. https://doi.org/10.6084/M9.FIGSHARE.C.4075553.V1. DOI: <a href="https://doi.org/10.6084/m9.figshare.c.4075553.v1" >10.6084/m9.figshare.c.4075553.v1</a> Handle: <a href="http://hdl.handle.net/10754/664504" >10754/664504</a></a></li></ul>
dc.date.published-online2018-05-23
dc.date.published-print2019-03
dc.date.posted2017-11-20


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