RUO Home

Repositorio Institucional de la Universidad de Oviedo

View Item 
  •   RUO Home
  • Producción Bibliográfica de UniOvi: RECOPILA
  • Artículos
  • View Item
  •   RUO Home
  • Producción Bibliográfica de UniOvi: RECOPILA
  • Artículos
  • View Item
    • español
    • English
JavaScript is disabled for your browser. Some features of this site may not work without it.

Browse

All of RUOCommunities and CollectionsBy Issue DateAuthorsTitlesSubjectsxmlui.ArtifactBrowser.Navigation.browse_issnAuthor profilesThis CollectionBy Issue DateAuthorsTitlesSubjectsxmlui.ArtifactBrowser.Navigation.browse_issn

My Account

LoginRegister

Statistics

View Usage Statistics

RECENTLY ADDED

Last submissions
Repository
How to publish
Resources
FAQs

M-estimators and trimmed means: from Hilbert-valued to fuzzy set-valued data

Author:
Sinova Fernández, BeatrizUniovi authority; Van Aelst, S.; Terán Agraz, Pedro NicolásUniovi authority
Publication date:
2020
Publisher version:
http://dx.doi.org/10.1007/s11634-020-00402-x
Citación:
Advances in Data Analysis and Classification, 15, p. 267–288 (2020); doi:10.1007/s11634-020-00402-x
URI:
http://hdl.handle.net/10651/56808
ISSN:
1862-5347
DOI:
10.1007/s11634-020-00402-x
Patrocinado por:

The research of Beatriz Sinova and Pedro Terán was partially supported by the Spanish Ministry of Economy and Competitiveness under Grant MTM2015-63971-P; and the Principality of Asturias/FEDER Funds under Grants GRUPIN14-101 and GRUPIN-IDI2018-000132. The research of Stefan Van Aelst was supported by Internal Funds KU Leuven (Belgium) under Grant C16/15/068. Their support is gratefully acknowledged.

Collections
  • Artículos [37541]
  • Estadística e Investigación Operativa [294]
  • Investigaciones y Documentos OpenAIRE [8401]
Files in this item
Thumbnail
untranslated
Postprint (284.5Kb)
Métricas
Compartir
Exportar a Mendeley
Estadísticas de uso
Estadísticas de uso
Metadata
Show full item record
Página principal Uniovi

Biblioteca

Contacto

Facebook Universidad de OviedoTwitter Universidad de Oviedo
The content of the Repository, unless otherwise specified, is protected with a Creative Commons license: Attribution-Non Commercial-No Derivatives 4.0 Internacional
Creative Commons Image