Estabilidade em análise de agrupamento (cluster analysis)

Detalhes bibliográficos
Ano de defesa: 2005
Autor(a) principal: ALBUQUERQUE, Mácio Augusto de lattes
Orientador(a): FERREIRA, Rinaldo Luiz Caraciolo
Banca de defesa: SANTOS, Eufrázio de Souza, LIRA JÚNIOR, Mário de Andrade
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal Rural de Pernambuco
Programa de Pós-Graduação: Programa de Pós-Graduação em Biometria e Estatística Aplicada
Departamento: Departamento de Estatística e Informática
País: Brasil
Palavras-chave em Português:
Palavras-chave em Inglês:
Área do conhecimento CNPq:
Link de acesso: http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/5178
Resumo: The main objective of this research was to propose a systematic to the study and interpretation of the stability of methods in cluster analysis through many cluster algorithms in vegetation data. The data set used came from a survey in the Silviculture Forest at Federal University of Viçosa – MG. To perform the cluster analysis the matrices of Mahalanobis distance were estimated based on the original data and by “bootstrap” resampling. Also the methods of single linkageage, complete linkageage, the average of the distances, the centroid, the medium and the Ward were used. For the detection of the association among the methods it was applied the chi-square test. For the various methods of clustering it was obtained a cofenetical correlation. The results of the associations of methods were very similar, indicating, in principle, that any algorithm of cluster studied is stabilized and exist, in fact, groups among the individuals analyzed. However, it was concluded that themethods coincide with themselves, except the methods of centroid and Ward. Also the centroid methods and average when compared to the Ward, respectively, based on the matrices of Mahalanobis starting from the original data set and “bootstrap”. The methodology proposed is promising to the study and interpretation of the stabilityof methods concerning the cluster analysis in vegetation data.