Cluster analysis applied to the Human Development Index (HDI) of Brazilian States
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Research, Society and Development |
Texto Completo: | https://rsdjournal.org/index.php/rsd/article/view/25747 |
Resumo: | This study aims to compare the performance of each method (hierarchical and non-hierarchical) of the grouping formed by several HDI from the 27 brazilian states, through the cluster analysis technique. As well as determining how many states there are in each formed group, to thus specify which technique best represents the data. Data from Atlas Brasil 2013 were used in relation to the 2010 HDI. For cluster analysis, the Mahalanobins matrix was used with the hierarchical method, from the data obtained, we applied the simple linkage methods, complete, average, ward liaison and a non-hierarchical method through the K-means method, the conphenetic correlation coefficient was also applied to measure the degree of fit between the original similar matrices and the resulting matrix of simplification provided by the grouping method. However, the method that best represents the data was the complete link. When grouping the states, the similarity between the HDI-R, HDI-L and HDI-S variables was considered this relationship formed similar groups between the connections from different regions of Brazil. |
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Cluster analysis applied to the Human Development Index (HDI) of Brazilian StatesAnálisis de conglomerados aplicado al Índice de Desarrollo Humano (IDH) de los Estados BrasileñosAnálise de agrupamento aplicado no Índice de Desenvolvimento Humano (IDH) dos Estados BrasileirosMahalanobinasMétodosEstados BrasileñosGrupo.MahalanobinsMétodosEstados brasileirosCluster.MahalanobinsMethodsBrazilian StatesCluster.This study aims to compare the performance of each method (hierarchical and non-hierarchical) of the grouping formed by several HDI from the 27 brazilian states, through the cluster analysis technique. As well as determining how many states there are in each formed group, to thus specify which technique best represents the data. Data from Atlas Brasil 2013 were used in relation to the 2010 HDI. For cluster analysis, the Mahalanobins matrix was used with the hierarchical method, from the data obtained, we applied the simple linkage methods, complete, average, ward liaison and a non-hierarchical method through the K-means method, the conphenetic correlation coefficient was also applied to measure the degree of fit between the original similar matrices and the resulting matrix of simplification provided by the grouping method. However, the method that best represents the data was the complete link. When grouping the states, the similarity between the HDI-R, HDI-L and HDI-S variables was considered this relationship formed similar groups between the connections from different regions of Brazil.El objetivo de este artículo es comparar el desempeño de cada método (jerárquico y no jerárquico) de agrupamiento formado por varios IDH de los 27 estados brasileños, a través de la técnica de análisis de conglomerados. También determina cuántos estados hay en cada grupo formado, con el fin de especificar qué técnica representa mejor los datos. Se utilizaron datos del Atlas Brasil 2013 en relación al IDH de 2010. Para el análisis de conglomerados se utilizó la matriz de Mahalanobins con el método jerárquico, a partir de los datos obtenidos, los métodos de simple, completo, promedio, ward binding y no -método jerárquico a través del método K-means, también se aplicó el coeficiente de correlación confenético para medir el grado de ajuste entre las matrices similares originales y la matriz resultante de la simplificación proporcionada por el método de agrupamiento. Sin embargo, el método que mejor representa los datos es el método de enlace completo. Al agrupar los estados, se tuvo en cuenta la similitud entre las variables IDH-R, IDH-L e IDH-S, relación que formó grupos similares entre conexiones de diferentes regiones de Brasil.O presente artigo tem por objetivo compara o desempenho de cada método (hierárquico e não hierárquico) de agrupamento formado por vários IDH dos 27 estados brasileiros, por meio da técnica de análise de agrupamento. Bem como determina quantos estados tem em cada grupo formado, para assim especificar qual técnica melhor representa os dados. Utilizou-se dados do Atlas Brasil 2013 com relação ao IDH de 2010. Para a análise de agrupamento foi utilizado a matriz de Mahalanobins com o método hierárquico, a partir dos dados obtidos, aplicou-se os métodos de ligação simples, completa, média, ligação de ward e um método não hierárquico através do método de K-means, também foram aplicados o coeficiente de correlação confénetica para medir o grau de ajuste entre as matrizes similares originais e a matriz resultante da simplificação proporcionada pelo método de agrupamento. No entanto foi verificado o método que melhor representa os dados é o de ligação completa. Ao agrupar os estados foi levado em consideração a semelhança entre as variáveis IDH-R, IDH-L e IDH-S está relação formou grupos semelhantes entre as ligações de diferentes regiões do Brasil. Research, Society and Development2022-01-24info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/2574710.33448/rsd-v11i2.25747Research, Society and Development; Vol. 11 No. 2; e18011225747Research, Society and Development; Vol. 11 Núm. 2; e18011225747Research, Society and Development; v. 11 n. 2; e180112257472525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIenghttps://rsdjournal.org/index.php/rsd/article/view/25747/22502Copyright (c) 2022 Emanuela Rodrigues do Nascimento; Mácio Augusto de Albuquerque; Kleber Napoleão Nunes de Oliveira Barros; Patrícia Silva Nascimento Barroshttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessNascimento, Emanuela Rodrigues do Albuquerque, Mácio Augusto de Barros, Kleber Napoleão Nunes de Oliveira Barros, Patrícia Silva Nascimento 2022-02-07T01:42:50Zoai:ojs.pkp.sfu.ca:article/25747Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:43:57.590148Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false |
dc.title.none.fl_str_mv |
Cluster analysis applied to the Human Development Index (HDI) of Brazilian States Análisis de conglomerados aplicado al Índice de Desarrollo Humano (IDH) de los Estados Brasileños Análise de agrupamento aplicado no Índice de Desenvolvimento Humano (IDH) dos Estados Brasileiros |
title |
Cluster analysis applied to the Human Development Index (HDI) of Brazilian States |
spellingShingle |
Cluster analysis applied to the Human Development Index (HDI) of Brazilian States Nascimento, Emanuela Rodrigues do Mahalanobinas Métodos Estados Brasileños Grupo. Mahalanobins Métodos Estados brasileiros Cluster. Mahalanobins Methods Brazilian States Cluster. |
title_short |
Cluster analysis applied to the Human Development Index (HDI) of Brazilian States |
title_full |
Cluster analysis applied to the Human Development Index (HDI) of Brazilian States |
title_fullStr |
Cluster analysis applied to the Human Development Index (HDI) of Brazilian States |
title_full_unstemmed |
Cluster analysis applied to the Human Development Index (HDI) of Brazilian States |
title_sort |
Cluster analysis applied to the Human Development Index (HDI) of Brazilian States |
author |
Nascimento, Emanuela Rodrigues do |
author_facet |
Nascimento, Emanuela Rodrigues do Albuquerque, Mácio Augusto de Barros, Kleber Napoleão Nunes de Oliveira Barros, Patrícia Silva Nascimento |
author_role |
author |
author2 |
Albuquerque, Mácio Augusto de Barros, Kleber Napoleão Nunes de Oliveira Barros, Patrícia Silva Nascimento |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Nascimento, Emanuela Rodrigues do Albuquerque, Mácio Augusto de Barros, Kleber Napoleão Nunes de Oliveira Barros, Patrícia Silva Nascimento |
dc.subject.por.fl_str_mv |
Mahalanobinas Métodos Estados Brasileños Grupo. Mahalanobins Métodos Estados brasileiros Cluster. Mahalanobins Methods Brazilian States Cluster. |
topic |
Mahalanobinas Métodos Estados Brasileños Grupo. Mahalanobins Métodos Estados brasileiros Cluster. Mahalanobins Methods Brazilian States Cluster. |
description |
This study aims to compare the performance of each method (hierarchical and non-hierarchical) of the grouping formed by several HDI from the 27 brazilian states, through the cluster analysis technique. As well as determining how many states there are in each formed group, to thus specify which technique best represents the data. Data from Atlas Brasil 2013 were used in relation to the 2010 HDI. For cluster analysis, the Mahalanobins matrix was used with the hierarchical method, from the data obtained, we applied the simple linkage methods, complete, average, ward liaison and a non-hierarchical method through the K-means method, the conphenetic correlation coefficient was also applied to measure the degree of fit between the original similar matrices and the resulting matrix of simplification provided by the grouping method. However, the method that best represents the data was the complete link. When grouping the states, the similarity between the HDI-R, HDI-L and HDI-S variables was considered this relationship formed similar groups between the connections from different regions of Brazil. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-24 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://rsdjournal.org/index.php/rsd/article/view/25747 10.33448/rsd-v11i2.25747 |
url |
https://rsdjournal.org/index.php/rsd/article/view/25747 |
identifier_str_mv |
10.33448/rsd-v11i2.25747 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://rsdjournal.org/index.php/rsd/article/view/25747/22502 |
dc.rights.driver.fl_str_mv |
https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
https://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 |
Research, Society and Development |
publisher.none.fl_str_mv |
Research, Society and Development |
dc.source.none.fl_str_mv |
Research, Society and Development; Vol. 11 No. 2; e18011225747 Research, Society and Development; Vol. 11 Núm. 2; e18011225747 Research, Society and Development; v. 11 n. 2; e18011225747 2525-3409 reponame:Research, Society and Development instname:Universidade Federal de Itajubá (UNIFEI) instacron:UNIFEI |
instname_str |
Universidade Federal de Itajubá (UNIFEI) |
instacron_str |
UNIFEI |
institution |
UNIFEI |
reponame_str |
Research, Society and Development |
collection |
Research, Society and Development |
repository.name.fl_str_mv |
Research, Society and Development - Universidade Federal de Itajubá (UNIFEI) |
repository.mail.fl_str_mv |
rsd.articles@gmail.com |
_version_ |
1797052703267880960 |