Modelling (and forecasting) extremes in time series: A naive approach

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dc.contributor.author	Neves, M.Manuela
dc.contributor.author	Cordeiro, Clara
dc.date.accessioned	2021-09-24T13:33:10Z
dc.date.available	2021-09-24T13:33:10Z
dc.date.issued	2020
dc.description.abstract	In Extreme Value Theory, we are essentially interested in the estimation of quantities related to extreme events. Whenever the focus is in large values, estimation is usually performed based on the largest k order statistics in the sample or on the excesses over a high level u. Here we are interested in modelling (and forecast- ing) extremes in time series. For modelling and forecasting classical time series, Boot.EXPOS is a computational procedure built in the R environment that has revealed to perform quite well in a large number of forecasting competitions. However, to deal with extreme values, a modification of that algorithm needs to be considered and is here under study	pt_PT
dc.description.version	N/A	pt_PT
dc.identifier.uri	http://hdl.handle.net/10400.5/21997
dc.language.iso	eng	pt_PT
dc.publisher	SPE	pt_PT
dc.subject	extreme value theory	pt_PT
dc.subject	extremal index estimation	pt_PT
dc.subject	re-sampling procedures;	pt_PT
dc.subject	time series	pt_PT
dc.title	Modelling (and forecasting) extremes in time series: A naive approach	pt_PT
dc.type	conference object
dspace.entity.type	Publication
oaire.citation.title	XXXIII Congresso da Sociedade Portuguesa de Estatística, Lisboa, 18-21 Outubro 2017	pt_PT
rcaap.rights	openAccess	pt_PT
rcaap.type	conferenceObject	pt_PT

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