Mostrar el registro sencillo del ítem

dc.contributor.author
Cook, R. Dennis  
dc.contributor.author
Forzani, Liliana Maria  
dc.date.available
2019-09-22T14:24:42Z  
dc.date.issued
2009-03  
dc.identifier.citation
Cook, R. Dennis; Forzani, Liliana Maria; Likelihood-Based Sufficient Dimension Reduction; American Statistical Association; Journal of The American Statistical Association; 104; 485; 3-2009; 197-208  
dc.identifier.issn
0162-1459  
dc.identifier.uri
http://hdl.handle.net/11336/84065  
dc.description.abstract
We obtain the maximum likelihood estimator of the central subspace under conditional normality of the predictors given the response. Analytically and in simulations we found that our new estimator can preform much better than sliced inverse regression, sliced average variance estimation and directional regression, and that it seems quite robust to deviations from normality.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
American Statistical Association  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Central Subspace  
dc.subject
Directional Regression  
dc.subject
Grassmann Manifolds  
dc.subject
Sliced Average Variance Estimation  
dc.subject
Sliced Inverse Regression  
dc.subject.classification
Estadística y Probabilidad  
dc.subject.classification
Matemáticas  
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS  
dc.title
Likelihood-Based Sufficient Dimension Reduction  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2019-09-20T14:17:30Z  
dc.journal.volume
104  
dc.journal.number
485  
dc.journal.pagination
197-208  
dc.journal.pais
Estados Unidos  
dc.journal.ciudad
Washington  
dc.description.fil
Fil: Cook, R. Dennis. University of Minnesota; Estados Unidos  
dc.description.fil
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  
dc.journal.title
Journal of The American Statistical Association  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1198/jasa.2009.0106  

Archivos asociados
Thumbnail
 
Tamaño: 301.5Kb
Formato: PDF
.