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dc.contributor.authorDagsvik, John K.
dc.contributor.authorFortuna, Mariachiara
dc.contributor.authorMoen, Sigmund Hov
dc.date.accessioned2020-04-21T08:26:27Z
dc.date.available2020-04-21T08:26:27Z
dc.date.created2020-04-20T14:59:44Z
dc.date.issued2020-03-20
dc.identifier.citationJournal of the Royal Statistical Society: Series A (Statistics in Society). 2020, .en_US
dc.identifier.issn0964-1998
dc.identifier.urihttps://hdl.handle.net/11250/2651801
dc.description.abstractThe paper analyses temperature data from 96 selected weather stations world wide, and from reconstructed northern hemisphere temperature data over the last two millennia. Using a non‐parametric test, we find that the stationarity hypothesis is not rejected by the data. Subsequently, we investigate further properties of the data by means of a statistical model known as the fractional Gaussian noise (FGN) model. Under stationarity FGN follows from the fact that the observed data are obtained as temporal aggregates of data generated at a finer (basic) timescale where temporal aggregation is taken over a ‘large’ number of basic units. The FGN process exhibits long‐range dependence. Several tests show that both the reconstructed and most of the observed data are consistent with the FGN model.en_US
dc.language.isoengen_US
dc.publisherWileyen_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.subjectTemperature changeen_US
dc.subjectFractional Gaussian noiseen_US
dc.subjectHurst indexen_US
dc.titleHow does temperature vary over time?: evidence on the stationary and fractal nature of temperature fluctuationsen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© 2020 The Authors. Journal of the Royal Statistical Society: Series A (Statistics in Society) Published by John Wiley & Sons Ltd on behalf of the Royal Statistical Society. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.en_US
dc.source.pagenumber26en_US
dc.source.volume183en
dc.source.journalJournal of the Royal Statistical Society: Series A (Statistics in Society)en_US
dc.source.issue3en_US
dc.identifier.doihttps://doi.org/10.1111/rssa.12557
dc.identifier.cristin1807169
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.fulltext
cristin.qualitycode1


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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
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