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dc.contributor.authorLangrock, Roland
dc.contributor.authorAdam, Timo
dc.contributor.authorLeos-Barajas, Vianey
dc.contributor.authorMews, Sina
dc.contributor.authorMiller, David L.
dc.contributor.authorPapastamatiou, Yannis P.
dc.date.accessioned2020-04-21T23:33:14Z
dc.date.available2020-04-21T23:33:14Z
dc.date.issued2018-08-01
dc.identifier.citationLangrock , R , Adam , T , Leos-Barajas , V , Mews , S , Miller , D L & Papastamatiou , Y P 2018 , ' Spline-based nonparametric inference in general state-switching models ' , Statistica Neerlandica , vol. 72 , no. 3 , pp. 179-200 . https://doi.org/10.1111/stan.12133en
dc.identifier.issn0039-0402
dc.identifier.otherPURE: 253097859
dc.identifier.otherPURE UUID: be5512a9-d930-4d45-a12f-f61650186545
dc.identifier.othercrossref: 10.1111/stan.12133
dc.identifier.otherScopus: 85050095311
dc.identifier.otherWOS: 000438904800002
dc.identifier.urihttps://hdl.handle.net/10023/19836
dc.description.abstractState‐switching models combine immense flexibility with relative mathematical simplicity and computational tractability and, as a consequence, have established themselves as general‐purpose models for time series data. In this paper, we provide an overview of ways to use penalized splines to allow for flexible nonparametric inference within state‐switching models, and provide a critical discussion of the use of corresponding classes of models. The methods are illustrated using animal acceleration data and energy price data.
dc.format.extent22
dc.language.isoeng
dc.relation.ispartofStatistica Neerlandicaen
dc.rights© 2018, the Authors, Statistica Neerlandica. This work has been made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1111/stan.12133en
dc.subjectHidden Markov modelen
dc.subjectMaximum penalized likelihooden
dc.subjectMarkov-switching regressionen
dc.subjectPenalized splinesen
dc.subjectHA Statisticsen
dc.subjectQA Mathematicsen
dc.subjectNDASen
dc.subject.lccHAen
dc.subject.lccQAen
dc.titleSpline-based nonparametric inference in general state-switching modelsen
dc.typeJournal articleen
dc.description.versionPostprinten
dc.contributor.institutionUniversity of St Andrews. School of Mathematics and Statisticsen
dc.contributor.institutionUniversity of St Andrews. Applied Mathematicsen
dc.contributor.institutionUniversity of St Andrews. Centre for Research into Ecological & Environmental Modellingen
dc.identifier.doihttps://doi.org/10.1111/stan.12133
dc.description.statusPeer revieweden
dc.date.embargoedUntil2020-04-22
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85050095311&partnerID=8YFLogxKen


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