Publicação
Testing Conditions and Estimating Parameters in Extreme Value Theory: Application to Environmental Data
| Resumo: | Extreme Value Theory has been asserting itself as one of the most important statistical theories for the applied sciences providing a solid theoretical basis for deriving statistical models describing extreme or even rare events. The efficiency of the inference and estimation procedures depends on the tail shape of the distribution underlying the data. In this work we will present a review of tests for assessing extreme value conditions and for the choice of the extreme value domain. Motivated by two real environmental problems we will apply those tests showing the need of performing such tests for choosing the most appropriate parameter estimation methods. |
|---|---|
| Autores principais: | Penalva , Helena |
| Outros Autores: | Prata Gomes , Dora; Manuela Neves , M.; Nunes , Sandra |
| Assunto: | environmental data extreme values heavy-tailed distributions semi-parametric estimation statistical testing |
| Ano: | 2019 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | unknown |
| Instituição associada: | Instituto Nacional de Estatística |
| Idioma: | inglês |
| Origem: | REVSTAT-Statistical Journal |
| _version_ | 1869319184285958144 |
|---|---|
| author | Penalva , Helena |
| author2 | Prata Gomes , Dora Manuela Neves , M. Nunes , Sandra |
| author2_role | author author author |
| author_facet | Penalva , Helena Prata Gomes , Dora Manuela Neves , M. Nunes , Sandra |
| author_role | author |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Penalva , Helena\"},{\"Person.name\":\"Prata Gomes , Dora\"},{\"Person.name\":\"Manuela Neves , M.\"},{\"Person.name\":\"Nunes , Sandra\"}] |
| datacite.creators.creator.creatorName.fl_str_mv | Penalva , Helena Prata Gomes , Dora Manuela Neves , M. Nunes , Sandra |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | environmental data extreme values heavy-tailed distributions semi-parametric estimation statistical testing |
| datacite.titles.title.fl_str_mv | Testing Conditions and Estimating Parameters in Extreme Value Theory: Application to Environmental Data |
| dc.creator.none.fl_str_mv | Penalva , Helena Prata Gomes , Dora Manuela Neves , M. Nunes , Sandra |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | https://doi.org/10.57805/revstat.v17i2.264 |
| dc.language.none.fl_str_mv | eng |
| dc.publisher.none.fl_str_mv | Statistics Portugal |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.source.none.fl_str_mv | REVSTAT-Statistical Journal; Vol. 17 No. 2 (2019): REVSTAT-Statistical Journal; 187-207 REVSTAT; Vol. 17 N.º 2 (2019): REVSTAT-Statistical Journal; 187-207 2183-0371 1645-6726 |
| dc.subject.none.fl_str_mv | environmental data extreme values heavy-tailed distributions semi-parametric estimation statistical testing |
| dc.title.fl_str_mv | Testing Conditions and Estimating Parameters in Extreme Value Theory: Application to Environmental Data |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_6501 |
| description | Extreme Value Theory has been asserting itself as one of the most important statistical theories for the applied sciences providing a solid theoretical basis for deriving statistical models describing extreme or even rare events. The efficiency of the inference and estimation procedures depends on the tail shape of the distribution underlying the data. In this work we will present a review of tests for assessing extreme value conditions and for the choice of the extreme value domain. Motivated by two real environmental problems we will apply those tests showing the need of performing such tests for choosing the most appropriate parameter estimation methods. |
| dirty | 0 |
| eu_rights_str_mv | unknown |
| format | article |
| id | revstat_dd0e8a1ef9a67341d125b55c968cee13 |
| identifier.doi.fl_str_mv | https://doi.org/10.57805/revstat.v17i2.264 |
| inst_facet_str | urn:organizationAcronym:revstat-statistical journal{{{_:::_}}}Instituto Nacional de Estatística |
| instacron_str | REVSTAT-Statistical Journal |
| institution | Instituto Nacional de Estatística |
| instname_str | Instituto Nacional de Estatística |
| language | eng |
| network_acronym_str | revstat |
| network_name_str | REVSTAT-Statistical Journal |
| oai_identifier_str | oai:revstat:article/264 |
| organization_str_mv | urn:organizationAcronym:revstat-statistical journal |
| person_str_mv | Penalva , Helena Prata Gomes , Dora Manuela Neves , M. Nunes , Sandra |
| publishDate | 2019 |
| publisher.none.fl_str_mv | Statistics Portugal |
| repo_facet_str | urn:repositoryAcronym:revstat{{{_:::_}}}REVSTAT-Statistical Journal |
| reponame_str | REVSTAT-Statistical Journal |
| repository_id_str | urn:repositoryAcronym:revstat |
| service_str_mv | urn:repositoryAcronym:revstat |
| spelling | en-USTesting Conditions and Estimating Parameters in Extreme Value Theory: Application to Environmental DataPenalva , HelenaPrata Gomes , DoraManuela Neves , M.Nunes , Sandraenvironmental dataextreme valuesheavy-tailed distributionssemi-parametric estimationstatistical testingCopyright (c) 2019 REVSTAT-Statistical Journalhttp://purl.org/coar/access_right/c_abf2https://creativecommons.org/licenses/by/4.0https://doi.org/10.57805/revstat.v17i2.264DOIoai:revstat:article/264OAIhttps://revstat.ine.pt/index.php/REVSTAT/article/view/264URLhttps://doi.org/10.57805/revstat.v17i2.264DOIhttps://revstat.ine.pt/index.php/REVSTAT/article/view/264/277URLHasVersion2019-04-22T00:00:00Zen-USExtreme Value Theory has been asserting itself as one of the most important statistical theories for the applied sciences providing a solid theoretical basis for deriving statistical models describing extreme or even rare events. The efficiency of the inference and estimation procedures depends on the tail shape of the distribution underlying the data. In this work we will present a review of tests for assessing extreme value conditions and for the choice of the extreme value domain. Motivated by two real environmental problems we will apply those tests showing the need of performing such tests for choosing the most appropriate parameter estimation methods.Statistics Portugalapplication/pdfen-USREVSTAT-Statistical Journal; Vol. 17 No. 2 (2019): REVSTAT-Statistical Journal; 187-207pt-PTREVSTAT; Vol. 17 N.º 2 (2019): REVSTAT-Statistical Journal; 187-2072183-03711645-6726engjournal articlehttp://purl.org/coar/resource_type/c_6501literatureVoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85 |
| spellingShingle | Testing Conditions and Estimating Parameters in Extreme Value Theory: Application to Environmental Data Penalva , Helena environmental data extreme values heavy-tailed distributions semi-parametric estimation statistical testing |
| status | SINGLETON |
| status_str | VoR |
| subject.fl_str_mv | environmental data extreme values heavy-tailed distributions semi-parametric estimation statistical testing |
| title | Testing Conditions and Estimating Parameters in Extreme Value Theory: Application to Environmental Data |
| title_full | Testing Conditions and Estimating Parameters in Extreme Value Theory: Application to Environmental Data |
| title_fullStr | Testing Conditions and Estimating Parameters in Extreme Value Theory: Application to Environmental Data |
| title_full_unstemmed | Testing Conditions and Estimating Parameters in Extreme Value Theory: Application to Environmental Data |
| title_short | Testing Conditions and Estimating Parameters in Extreme Value Theory: Application to Environmental Data |
| title_sort | Testing Conditions and Estimating Parameters in Extreme Value Theory: Application to Environmental Data |
| topic | environmental data extreme values heavy-tailed distributions semi-parametric estimation statistical testing |
| topic_facet | environmental data extreme values heavy-tailed distributions semi-parametric estimation statistical testing |
| url | https://doi.org/10.57805/revstat.v17i2.264 |
| visible | 1 |