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A maximal inequality for dependent random variables

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Resumo:For a sequence {Xn,n⩾1} of random variables satisfying E|Xn|<∞ for all n⩾1, a maximal inequality is established, and used to obtain strong law of large numbers for dependent random variables.
Autores principais:Lita da Silva, João
Assunto:Dependent random variables Maximal inequality Strong law of large numbers Analysis Algebra and Number Theory Geometry and Topology Computational Mathematics Applied Mathematics
Ano:2025
País:Portugal
Tipo de documento:artigo
Tipo de acesso:acesso aberto
Instituição associada:Universidade Nova de Lisboa
Idioma:inglês
Origem:Repositório Institucional da UNL
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author Lita da Silva, João
author_facet Lita da Silva, João
author_role author
contributor_name_str_mv DM - Departamento de Matemática
GeoBioTec - Geobiociências, Geoengenharias e Geotecnologias
Springer-Verlag Italia
RUN
country_str PT
creators_json_txt [{\"Person.name\":\"Lita da Silva, João\"}]
datacite.contributors.contributor.contributorName.fl_str_mv DM - Departamento de Matemática
GeoBioTec - Geobiociências, Geoengenharias e Geotecnologias
Springer-Verlag Italia
RUN
datacite.creators.creator.creatorName.fl_str_mv Lita da Silva, João
datacite.date.Accepted.fl_str_mv 2025-02-20T00:00:00Z
datacite.rights.fl_str_mv http://purl.org/coar/access_right/c_abf2
datacite.subjects.subject.fl_str_mv Dependent random variables
Maximal inequality
Strong law of large numbers
Analysis
Algebra and Number Theory
Geometry and Topology
Computational Mathematics
Applied Mathematics
datacite.titles.title.fl_str_mv A maximal inequality for dependent random variables
dc.contributor.none.fl_str_mv DM - Departamento de Matemática
GeoBioTec - Geobiociências, Geoengenharias e Geotecnologias
Springer-Verlag Italia
RUN
dc.creator.none.fl_str_mv Lita da Silva, João
dc.date.Accepted.fl_str_mv 2025-02-20T00:00:00Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv http://hdl.handle.net/10362/184283
dc.language.none.fl_str_mv eng
dc.rights.none.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.subject.none.fl_str_mv Dependent random variables
Maximal inequality
Strong law of large numbers
Analysis
Algebra and Number Theory
Geometry and Topology
Computational Mathematics
Applied Mathematics
dc.title.fl_str_mv A maximal inequality for dependent random variables
dc.type.none.fl_str_mv http://purl.org/coar/resource_type/c_6501
description For a sequence {Xn,n⩾1} of random variables satisfying E|Xn|<∞ for all n⩾1, a maximal inequality is established, and used to obtain strong law of large numbers for dependent random variables.
dirty 0
eu_rights_str_mv openAccess
format article
fulltext.url.fl_str_mv https://run.unl.pt/bitstreams/4b575335-1167-46aa-aa47-e0978e460622/download
funding.funder.alternateName_str_mv FCT
funding.funder.identifier_str_mv http://doi.org/10.13039/501100001871
funding.funder.name_str_mv Fundação para a Ciência e a Tecnologia
funding.name_str_mv 6817 - DCRRNI ID
id run_bef4befa154eae3951dbf2e2e4bd9489
identifier.url.fl_str_mv http://hdl.handle.net/10362/184283
instacron_str unl
institution Universidade Nova de Lisboa
instname_str Universidade Nova de Lisboa
language eng
network_acronym_str run
network_name_str Repositório Institucional da UNL
oai_identifier_str oai:run.unl.pt:10362/184283
organization_str_mv urn:organizationAcronym:unl
person_str_mv Lita da Silva, João
publishDate 2025
reponame_str Repositório Institucional da UNL
repository_id_str urn:repositoryAcronym:run
service_str_mv urn:repositoryAcronym:run
spelling engenFor a sequence {Xn,n⩾1} of random variables satisfying E|Xn|<∞ for all n⩾1, a maximal inequality is established, and used to obtain strong law of large numbers for dependent random variables.application/pdfenA maximal inequality for dependent random variablesLita da Silva, JoãoDM - Departamento de MatemáticaGeoBioTec - Geobiociências, Geoengenharias e GeotecnologiasSpringer-Verlag ItaliaHostingInstitutionOrganizationalRUNe-mailmailto:run@unl.ptrun@unl.ptISSNIsPartOf1578-7303URNIsPartOfPURE: 118928040URNIsPartOfPURE UUID: 25359046-d9ca-4c86-a683-c4d732291847URNIsPartOfScopus: 85218420847URNIsPartOfWOS: 001427957700001DOIIsPartOf10.1007/s13398-025-01709-02025-02-202025-02-20T00:00:00ZHandlehttp://hdl.handle.net/10362/184283http://purl.org/coar/access_right/c_abf2open accessDependent random variablesMaximal inequalityStrong law of large numbersAnalysisAlgebra and Number TheoryGeometry and TopologyComputational MathematicsApplied Mathematics247385 bytesFundação para a Ciência e a TecnologiaGeoBioSciences GeoTechnologies and GeoEngineering6817 - DCRRNI IDCrossref Funder IDhttp://doi.org/10.13039/501100001871literaturehttp://purl.org/coar/resource_type/c_6501journal articlehttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://run.unl.pt/bitstreams/4b575335-1167-46aa-aa47-e0978e460622/download
spellingShingle A maximal inequality for dependent random variables
Lita da Silva, João
Dependent random variables
Maximal inequality
Strong law of large numbers
Analysis
Algebra and Number Theory
Geometry and Topology
Computational Mathematics
Applied Mathematics
status SINGLETON
subject.fl_str_mv Dependent random variables
Maximal inequality
Strong law of large numbers
Analysis
Algebra and Number Theory
Geometry and Topology
Computational Mathematics
Applied Mathematics
title A maximal inequality for dependent random variables
title_full A maximal inequality for dependent random variables
title_fullStr A maximal inequality for dependent random variables
title_full_unstemmed A maximal inequality for dependent random variables
title_short A maximal inequality for dependent random variables
title_sort A maximal inequality for dependent random variables
topic Dependent random variables
Maximal inequality
Strong law of large numbers
Analysis
Algebra and Number Theory
Geometry and Topology
Computational Mathematics
Applied Mathematics
topic_facet Dependent random variables
Maximal inequality
Strong law of large numbers
Analysis
Algebra and Number Theory
Geometry and Topology
Computational Mathematics
Applied Mathematics
url http://hdl.handle.net/10362/184283
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