Kernel density estimation with doubly truncated data

Detalhes bibliográficos
Autor(a) principal: Moreira, Carla
Data de Publicação: 2011
Outros Autores: Uña Álvarez, Jacobo de
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/1822/21037
Resumo: In some applications with astronomical and survival data, doubly truncated data are sometimes encountered. In this work we introduce kernel-type density estimation for a random variable which is sampled under random double truncation. Two different estimators are considered. As usual, the estimators are defined as a convolution between a kernel function and an estimator of the cumulative distribution function, which may be the NPMLE [2] or a semiparametric estimator [9]. Asymptotic properties of the introduced estimators are explored. Their finite sample behaviour is investigated through simulations. Real data illustration is included.
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spelling Kernel density estimation with doubly truncated dataBiased samplingDouble truncationIn some applications with astronomical and survival data, doubly truncated data are sometimes encountered. In this work we introduce kernel-type density estimation for a random variable which is sampled under random double truncation. Two different estimators are considered. As usual, the estimators are defined as a convolution between a kernel function and an estimator of the cumulative distribution function, which may be the NPMLE [2] or a semiparametric estimator [9]. Asymptotic properties of the introduced estimators are explored. Their finite sample behaviour is investigated through simulations. Real data illustration is included.Fundação para a Ciência e a Tecnologia (FCT)Spanish Ministerio de Ciencia e InnovaciónUniversidade do MinhoMoreira, CarlaUña Álvarez, Jacobo de2011-092011-09-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/21037eng1935-7524http://projecteuclid.org/euclid.ejs/1333113100info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:50:19Zoai:repositorium.sdum.uminho.pt:1822/21037Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:48:58.963896Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Kernel density estimation with doubly truncated data
title Kernel density estimation with doubly truncated data
spellingShingle Kernel density estimation with doubly truncated data
Moreira, Carla
Biased sampling
Double truncation
title_short Kernel density estimation with doubly truncated data
title_full Kernel density estimation with doubly truncated data
title_fullStr Kernel density estimation with doubly truncated data
title_full_unstemmed Kernel density estimation with doubly truncated data
title_sort Kernel density estimation with doubly truncated data
author Moreira, Carla
author_facet Moreira, Carla
Uña Álvarez, Jacobo de
author_role author
author2 Uña Álvarez, Jacobo de
author2_role author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Moreira, Carla
Uña Álvarez, Jacobo de
dc.subject.por.fl_str_mv Biased sampling
Double truncation
topic Biased sampling
Double truncation
description In some applications with astronomical and survival data, doubly truncated data are sometimes encountered. In this work we introduce kernel-type density estimation for a random variable which is sampled under random double truncation. Two different estimators are considered. As usual, the estimators are defined as a convolution between a kernel function and an estimator of the cumulative distribution function, which may be the NPMLE [2] or a semiparametric estimator [9]. Asymptotic properties of the introduced estimators are explored. Their finite sample behaviour is investigated through simulations. Real data illustration is included.
publishDate 2011
dc.date.none.fl_str_mv 2011-09
2011-09-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1822/21037
url http://hdl.handle.net/1822/21037
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1935-7524
http://projecteuclid.org/euclid.ejs/1333113100
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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