Publicação
Modelling (and forecasting) extremes in time series: A naive approach
| Resumo: | 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 |
|---|---|
| Autores principais: | Neves, M.Manuela |
| Outros Autores: | Cordeiro, Clara |
| Assunto: | extreme value theory extremal index estimation re-sampling procedures; time series |
| Ano: | 2020 |
| País: | Portugal |
| Tipo de documento: | documento de conferência |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório da Universidade de Lisboa |
| _version_ | 1865920781863616512 |
|---|---|
| author | Neves, M.Manuela |
| author2 | Cordeiro, Clara |
| author2_role | author |
| author_facet | Neves, M.Manuela Neves, M.Manuela Cordeiro, Clara Cordeiro, Clara |
| author_role | author |
| contributor_name_str_mv | Repositório Científico de Acesso Aberto da ULisboa |
| country_str | PT |
| creators_json_str | [{\"Person.name\":\"Neves, M.Manuela\"},{\"Person.name\":\"Cordeiro, Clara\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Repositório Científico de Acesso Aberto da ULisboa |
| datacite.creators.creator.creatorName.fl_str_mv | Neves, M.Manuela Cordeiro, Clara |
| datacite.date.Accepted.fl_str_mv | 2020-01-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2021-09-24T13:33:10Z |
| datacite.date.embargoed.fl_str_mv | 2021-09-24T13:33:10Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | extreme value theory extremal index estimation re-sampling procedures; time series |
| datacite.titles.title.fl_str_mv | Modelling (and forecasting) extremes in time series: A naive approach |
| dc.contributor.none.fl_str_mv | Repositório Científico de Acesso Aberto da ULisboa |
| dc.creator.none.fl_str_mv | Neves, M.Manuela Cordeiro, Clara |
| dc.date.Accepted.fl_str_mv | 2020-01-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2021-09-24T13:33:10Z |
| dc.date.embargoed.fl_str_mv | 2021-09-24T13:33:10Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10400.5/21997 |
| dc.language.none.fl_str_mv | eng |
| dc.publisher.none.fl_str_mv | SPE |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | extreme value theory extremal index estimation re-sampling procedures; time series |
| dc.title.fl_str_mv | Modelling (and forecasting) extremes in time series: A naive approach |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_c94f |
| description | 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 |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | conferenceObject |
| fulltext.url.fl_str_mv | https://repositorio.ulisboa.pt/bitstreams/0cec170c-74ef-45b0-9d61-d225ad212c5f/download |
| id | ul_2dedd50cb89cc3a418cd15fb7e9f75fe |
| identifier.url.fl_str_mv | http://hdl.handle.net/10400.5/21997 |
| instacron_str | ul |
| institution | Universidade de Lisboa |
| instname_str | Universidade de Lisboa |
| language | eng |
| network_acronym_str | ul |
| network_name_str | Repositório da Universidade de Lisboa |
| oai_identifier_str | oai:repositorio.ulisboa.pt:10400.5/21997 |
| organization_str_mv | urn:organizationAcronym:ul |
| person_str_mv | Neves, M.Manuela Cordeiro, Clara |
| publishDate | 2020 |
| publisher.none.fl_str_mv | SPE |
| reponame_str | Repositório da Universidade de Lisboa |
| repository_id_str | urn:repositoryAcronym:ul |
| service_str_mv | urn:repositoryAcronym:ul |
| spelling | engSPEpt_PTIn 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 studyapplication/pdfpt_PTModelling (and forecasting) extremes in time series: A naive approachNeves, M.ManuelaCordeiro, ClaraHostingInstitutionOrganizationalRepositório Científico de Acesso Aberto da ULisboae-mailmailto:repositorio@reitoria.ulisboa.ptrepositorio@reitoria.ulisboa.pt2021-09-24T13:33:10Z20202020-01-01T00:00:00ZHandlehttp://hdl.handle.net/10400.5/21997http://purl.org/coar/access_right/c_abf2open accessextreme value theoryextremal index estimationre-sampling procedures;time series306194 bytesother research producthttp://purl.org/coar/resource_type/c_c94fconference objecthttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://repositorio.ulisboa.pt/bitstreams/0cec170c-74ef-45b0-9d61-d225ad212c5f/downloadXXXIII Congresso da Sociedade Portuguesa de Estatística, Lisboa, 18-21 Outubro 2017 |
| spellingShingle | Modelling (and forecasting) extremes in time series: A naive approach Modelling (and forecasting) extremes in time series: A naive approach Neves, M.Manuela extreme value theory extremal index estimation re-sampling procedures; time series Neves, M.Manuela extreme value theory extremal index estimation re-sampling procedures; time series |
| status | SINGLETON |
| subject.fl_str_mv | extreme value theory extremal index estimation re-sampling procedures; time series |
| title | Modelling (and forecasting) extremes in time series: A naive approach |
| title_full | Modelling (and forecasting) extremes in time series: A naive approach |
| title_fullStr | Modelling (and forecasting) extremes in time series: A naive approach Modelling (and forecasting) extremes in time series: A naive approach |
| title_full_unstemmed | Modelling (and forecasting) extremes in time series: A naive approach Modelling (and forecasting) extremes in time series: A naive approach |
| title_short | Modelling (and forecasting) extremes in time series: A naive approach |
| title_sort | Modelling (and forecasting) extremes in time series: A naive approach |
| topic | extreme value theory extremal index estimation re-sampling procedures; time series |
| topic_facet | extreme value theory extremal index estimation re-sampling procedures; time series |
| url | http://hdl.handle.net/10400.5/21997 |
| visible | 1 |