Clustering of Small Territories Based on Axes of Inequality

In the present paper, we conduct a study before creating an e-cohort for the design of the sample. This e-cohort had to enable the effective representation of the province of Girona to facilitate its study according to the axes of inequality. Methods: The territory under study is divided by municipa...

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Detalles Bibliográficos
Autores: Perafita Basart, Xavier, Sáez Zafra, Marc
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10256/20730
Acceso en línea:http://hdl.handle.net/10256/20730
Access Level:acceso abierto
Palabra clave:Dades massives
Big data
Anàlisi de conglomerats
Cluster analysis
Desigualtat social -- Mètodes estadístics
Equality -- Statistical methods
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spelling Clustering of Small Territories Based on Axes of InequalityPerafita Basart, XavierSáez Zafra, MarcDades massivesBig dataAnàlisi de conglomeratsCluster analysisDesigualtat social -- Mètodes estadísticsEquality -- Statistical methodsIn the present paper, we conduct a study before creating an e-cohort for the design of the sample. This e-cohort had to enable the effective representation of the province of Girona to facilitate its study according to the axes of inequality. Methods: The territory under study is divided by municipalities, considering these different axes. The study consists of a comparison of 14 clustering algorithms, together with 3 data sets of municipal information to detect the grouping that was the most consistent. Prior to carrying out the clustering, a variable selection process was performed to discard those that were not useful. The comparison was carried out following two axes: results and graphical representation. Results: The intra-cluster results were also analyzed to observe the coherence of the grouping. Finally, we study the probability of belonging to a cluster, such as the one containing the county capital. Conclusions: This clustering can be the basis for working with a sample that is significant and representative of the territoryMDPI (Multidisciplinary Digital Publishing Institute)2022info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionpeer-reviewedapplication/pdfhttp://hdl.handle.net/10256/20730http://hdl.handle.net/10256/20730International Journal of Environmental Research and Public Health, 2022, vol. 19, núm. 6, p. 3359Articles publicats (D-EC)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)Inglésinfo:eu-repo/semantics/altIdentifier/doi/10.3390/ijerph19063359info:eu-repo/semantics/altIdentifier/eissn/1660-4601Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:10256/207302026-05-29T05:05:01Z
dc.title.none.fl_str_mv Clustering of Small Territories Based on Axes of Inequality
title Clustering of Small Territories Based on Axes of Inequality
spellingShingle Clustering of Small Territories Based on Axes of Inequality
Perafita Basart, Xavier
Dades massives
Big data
Anàlisi de conglomerats
Cluster analysis
Desigualtat social -- Mètodes estadístics
Equality -- Statistical methods
title_short Clustering of Small Territories Based on Axes of Inequality
title_full Clustering of Small Territories Based on Axes of Inequality
title_fullStr Clustering of Small Territories Based on Axes of Inequality
title_full_unstemmed Clustering of Small Territories Based on Axes of Inequality
title_sort Clustering of Small Territories Based on Axes of Inequality
dc.creator.none.fl_str_mv Perafita Basart, Xavier
Sáez Zafra, Marc
author Perafita Basart, Xavier
author_facet Perafita Basart, Xavier
Sáez Zafra, Marc
author_role author
author2 Sáez Zafra, Marc
author2_role author
dc.subject.none.fl_str_mv Dades massives
Big data
Anàlisi de conglomerats
Cluster analysis
Desigualtat social -- Mètodes estadístics
Equality -- Statistical methods
topic Dades massives
Big data
Anàlisi de conglomerats
Cluster analysis
Desigualtat social -- Mètodes estadístics
Equality -- Statistical methods
description In the present paper, we conduct a study before creating an e-cohort for the design of the sample. This e-cohort had to enable the effective representation of the province of Girona to facilitate its study according to the axes of inequality. Methods: The territory under study is divided by municipalities, considering these different axes. The study consists of a comparison of 14 clustering algorithms, together with 3 data sets of municipal information to detect the grouping that was the most consistent. Prior to carrying out the clustering, a variable selection process was performed to discard those that were not useful. The comparison was carried out following two axes: results and graphical representation. Results: The intra-cluster results were also analyzed to observe the coherence of the grouping. Finally, we study the probability of belonging to a cluster, such as the one containing the county capital. Conclusions: This clustering can be the basis for working with a sample that is significant and representative of the territory
publishDate 2022
dc.date.none.fl_str_mv 2022
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
peer-reviewed
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10256/20730
http://hdl.handle.net/10256/20730
url http://hdl.handle.net/10256/20730
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.3390/ijerph19063359
info:eu-repo/semantics/altIdentifier/eissn/1660-4601
dc.rights.none.fl_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI (Multidisciplinary Digital Publishing Institute)
publisher.none.fl_str_mv MDPI (Multidisciplinary Digital Publishing Institute)
dc.source.none.fl_str_mv International Journal of Environmental Research and Public Health, 2022, vol. 19, núm. 6, p. 3359
Articles publicats (D-EC)
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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