Clustering of Small Territories Based on Axes of Inequality
dc.contributor.author
dc.date.accessioned
2022-03-14T07:35:00Z
dc.date.available
2022-03-14T07:35:00Z
dc.date.issued
2022-03-12
dc.identifier.uri
dc.description.abstract
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
dc.format.mimetype
application/pdf
dc.language.iso
eng
dc.publisher
MDPI (Multidisciplinary Digital Publishing Institute)
dc.relation.isformatof
Reproducció digital del document publicat a: https://doi.org/10.3390/ijerph19063359
dc.relation.ispartof
International Journal of Environmental Research and Public Health, 2022, vol. 19, núm. 6, p. 3359
dc.relation.ispartofseries
Articles publicats (D-EC)
dc.rights
Attribution 4.0 International
dc.rights.uri
dc.subject
dc.title
Clustering of Small Territories Based on Axes of Inequality
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/openAccess
dc.type.version
info:eu-repo/semantics/publishedVersion
dc.identifier.doi
dc.type.peerreviewed
peer-reviewed
dc.identifier.eissn
1660-4601