LDR: A Package for Likelihood-Based Sufficient Dimension Reduction
- Autores
- Cook, R. Dennis; Forzani, Liliana Maria; Tomassi, Diego Rodolfo
- Año de publicación
- 2011
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- We introduce a new MATLAB software package that implements several recently proposed likelihood-based methods for sufficient dimension reduction. Current capabilities include estimation of reduced subspaces with a fixed dimension d, as well as estimation of d by use of likelihood-ratio testing, permutation testing and information criteria. The methods are suitable for preprocessing data for both regression and classification. Implementations of related estimators are also available. Although the software is more oriented to command-line operation, a graphical user interface is also provided for prototype computations.
Fil: Cook, R. Dennis. University of Minnesota; Estados Unidos
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: Tomassi, Diego Rodolfo. 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 - Materia
-
DIMENSION REDUCTION
INVERSE REGRESSION
PRINCIPAL COMPONENTS - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/67947
Ver los metadatos del registro completo
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LDR: A Package for Likelihood-Based Sufficient Dimension ReductionCook, R. DennisForzani, Liliana MariaTomassi, Diego RodolfoDIMENSION REDUCTIONINVERSE REGRESSIONPRINCIPAL COMPONENTShttps://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1We introduce a new MATLAB software package that implements several recently proposed likelihood-based methods for sufficient dimension reduction. Current capabilities include estimation of reduced subspaces with a fixed dimension d, as well as estimation of d by use of likelihood-ratio testing, permutation testing and information criteria. The methods are suitable for preprocessing data for both regression and classification. Implementations of related estimators are also available. Although the software is more oriented to command-line operation, a graphical user interface is also provided for prototype computations.Fil: Cook, R. Dennis. University of Minnesota; Estados UnidosFil: 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: Tomassi, Diego Rodolfo. 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; ArgentinaJournal Statistical Software2011-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/67947Cook, R. Dennis; Forzani, Liliana Maria; Tomassi, Diego Rodolfo; LDR: A Package for Likelihood-Based Sufficient Dimension Reduction; Journal Statistical Software; Journal Of Statistical Software; 39; 3; 3-2011; 1-11548-7660CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.jstatsoft.org/article/view/v039i03info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:29:08Zoai:ri.conicet.gov.ar:11336/67947instacron: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:34982025-10-22 11:29:09.167CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
LDR: A Package for Likelihood-Based Sufficient Dimension Reduction |
title |
LDR: A Package for Likelihood-Based Sufficient Dimension Reduction |
spellingShingle |
LDR: A Package for Likelihood-Based Sufficient Dimension Reduction Cook, R. Dennis DIMENSION REDUCTION INVERSE REGRESSION PRINCIPAL COMPONENTS |
title_short |
LDR: A Package for Likelihood-Based Sufficient Dimension Reduction |
title_full |
LDR: A Package for Likelihood-Based Sufficient Dimension Reduction |
title_fullStr |
LDR: A Package for Likelihood-Based Sufficient Dimension Reduction |
title_full_unstemmed |
LDR: A Package for Likelihood-Based Sufficient Dimension Reduction |
title_sort |
LDR: A Package for Likelihood-Based Sufficient Dimension Reduction |
dc.creator.none.fl_str_mv |
Cook, R. Dennis Forzani, Liliana Maria Tomassi, Diego Rodolfo |
author |
Cook, R. Dennis |
author_facet |
Cook, R. Dennis Forzani, Liliana Maria Tomassi, Diego Rodolfo |
author_role |
author |
author2 |
Forzani, Liliana Maria Tomassi, Diego Rodolfo |
author2_role |
author author |
dc.subject.none.fl_str_mv |
DIMENSION REDUCTION INVERSE REGRESSION PRINCIPAL COMPONENTS |
topic |
DIMENSION REDUCTION INVERSE REGRESSION PRINCIPAL COMPONENTS |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.1 https://purl.org/becyt/ford/1 |
dc.description.none.fl_txt_mv |
We introduce a new MATLAB software package that implements several recently proposed likelihood-based methods for sufficient dimension reduction. Current capabilities include estimation of reduced subspaces with a fixed dimension d, as well as estimation of d by use of likelihood-ratio testing, permutation testing and information criteria. The methods are suitable for preprocessing data for both regression and classification. Implementations of related estimators are also available. Although the software is more oriented to command-line operation, a graphical user interface is also provided for prototype computations. Fil: Cook, R. Dennis. University of Minnesota; Estados Unidos 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: Tomassi, Diego Rodolfo. 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 |
description |
We introduce a new MATLAB software package that implements several recently proposed likelihood-based methods for sufficient dimension reduction. Current capabilities include estimation of reduced subspaces with a fixed dimension d, as well as estimation of d by use of likelihood-ratio testing, permutation testing and information criteria. The methods are suitable for preprocessing data for both regression and classification. Implementations of related estimators are also available. Although the software is more oriented to command-line operation, a graphical user interface is also provided for prototype computations. |
publishDate |
2011 |
dc.date.none.fl_str_mv |
2011-03 |
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/11336/67947 Cook, R. Dennis; Forzani, Liliana Maria; Tomassi, Diego Rodolfo; LDR: A Package for Likelihood-Based Sufficient Dimension Reduction; Journal Statistical Software; Journal Of Statistical Software; 39; 3; 3-2011; 1-1 1548-7660 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/67947 |
identifier_str_mv |
Cook, R. Dennis; Forzani, Liliana Maria; Tomassi, Diego Rodolfo; LDR: A Package for Likelihood-Based Sufficient Dimension Reduction; Journal Statistical Software; Journal Of Statistical Software; 39; 3; 3-2011; 1-1 1548-7660 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/https://www.jstatsoft.org/article/view/v039i03 |
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 |
dc.publisher.none.fl_str_mv |
Journal Statistical Software |
publisher.none.fl_str_mv |
Journal Statistical Software |
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 |
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1846781874879332352 |
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13.229304 |