On local times, density estimation and supervised classification from functional data

Autores
Llop Orzan, Pamela Nerina; Forzani, Liliana Maria; Fraiman, Jacob Ricardo
Año de publicación
2011
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this paper, we define a n-consistent nonparametric estimator for the marginal density function of an order one stationary process built up from a sample of i.i.d continuous time trajectories. Under mild conditions we obtain strong consistency, strong orders of convergence and derive the asymptotic distribution of the estimator. We extend some of the results to the non-stationary case. We propose a nonparametric classification rule based on local times (occupation measure) and include some simulations studies.
Fil: Llop Orzan, Pamela Nerina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; Argentina
Fil: Forzani, Liliana Maria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; Argentina
Fil: Fraiman, Jacob Ricardo. Universidad de la República; Uruguay
Materia
Functional Data
Density Estimation
Nearest Neighbor
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/67964
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/67964
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling On local times, density estimation and supervised classification from functional dataLlop Orzan, Pamela NerinaForzani, Liliana MariaFraiman, Jacob RicardoFunctional DataDensity EstimationNearest Neighborhttps://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1In this paper, we define a n-consistent nonparametric estimator for the marginal density function of an order one stationary process built up from a sample of i.i.d continuous time trajectories. Under mild conditions we obtain strong consistency, strong orders of convergence and derive the asymptotic distribution of the estimator. We extend some of the results to the non-stationary case. We propose a nonparametric classification rule based on local times (occupation measure) and include some simulations studies.Fil: Llop Orzan, Pamela Nerina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; ArgentinaFil: Forzani, Liliana Maria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; ArgentinaFil: Fraiman, Jacob Ricardo. Universidad de la República; UruguayElsevier Inc2011-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/67964Llop Orzan, Pamela Nerina; Forzani, Liliana Maria; Fraiman, Jacob Ricardo; On local times, density estimation and supervised classification from functional data; Elsevier Inc; Journal Of Multivariate Analysis; 102; 1; 1-2011; 73-860047-259XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.jmva.2010.08.002info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:43:34Zoai:ri.conicet.gov.ar:11336/67964instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:43:35.084CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv On local times, density estimation and supervised classification from functional data
title On local times, density estimation and supervised classification from functional data
spellingShingle On local times, density estimation and supervised classification from functional data
Llop Orzan, Pamela Nerina
Functional Data
Density Estimation
Nearest Neighbor
title_short On local times, density estimation and supervised classification from functional data
title_full On local times, density estimation and supervised classification from functional data
title_fullStr On local times, density estimation and supervised classification from functional data
title_full_unstemmed On local times, density estimation and supervised classification from functional data
title_sort On local times, density estimation and supervised classification from functional data
dc.creator.none.fl_str_mv Llop Orzan, Pamela Nerina
Forzani, Liliana Maria
Fraiman, Jacob Ricardo
author Llop Orzan, Pamela Nerina
author_facet Llop Orzan, Pamela Nerina
Forzani, Liliana Maria
Fraiman, Jacob Ricardo
author_role author
author2 Forzani, Liliana Maria
Fraiman, Jacob Ricardo
author2_role author
author
dc.subject.none.fl_str_mv Functional Data
Density Estimation
Nearest Neighbor
topic Functional Data
Density Estimation
Nearest Neighbor
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.1
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv In this paper, we define a n-consistent nonparametric estimator for the marginal density function of an order one stationary process built up from a sample of i.i.d continuous time trajectories. Under mild conditions we obtain strong consistency, strong orders of convergence and derive the asymptotic distribution of the estimator. We extend some of the results to the non-stationary case. We propose a nonparametric classification rule based on local times (occupation measure) and include some simulations studies.
Fil: Llop Orzan, Pamela Nerina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; Argentina
Fil: Forzani, Liliana Maria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; Argentina
Fil: Fraiman, Jacob Ricardo. Universidad de la República; Uruguay
description In this paper, we define a n-consistent nonparametric estimator for the marginal density function of an order one stationary process built up from a sample of i.i.d continuous time trajectories. Under mild conditions we obtain strong consistency, strong orders of convergence and derive the asymptotic distribution of the estimator. We extend some of the results to the non-stationary case. We propose a nonparametric classification rule based on local times (occupation measure) and include some simulations studies.
publishDate 2011
dc.date.none.fl_str_mv 2011-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/67964
Llop Orzan, Pamela Nerina; Forzani, Liliana Maria; Fraiman, Jacob Ricardo; On local times, density estimation and supervised classification from functional data; Elsevier Inc; Journal Of Multivariate Analysis; 102; 1; 1-2011; 73-86
0047-259X
CONICET Digital
CONICET
url http://hdl.handle.net/11336/67964
identifier_str_mv Llop Orzan, Pamela Nerina; Forzani, Liliana Maria; Fraiman, Jacob Ricardo; On local times, density estimation and supervised classification from functional data; Elsevier Inc; Journal Of Multivariate Analysis; 102; 1; 1-2011; 73-86
0047-259X
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jmva.2010.08.002
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Inc
publisher.none.fl_str_mv Elsevier Inc
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1844614471727710208
score 13.070432

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