Efeito de Diferentes Estruturas de Correlação nos Ângulos Formados entre Componentes Principais e Interpretáveis em Amostras com Presença de Pontos Discrepantes
DOI:
https://doi.org/10.5902/2179460X12564Abstract
Análise de Componentes Principais (ACP) tem como objetivo descrever a estrutura de covariâncias de um vetor aleatório utilizando combinações lineares das variáveis originais. Em algumas situações, os coeficientes dos Componentes Principais (CP) podem não ser facilmente interpretados devido ao número de variáveis ou presença de pontos discrepantes. Assim foram introduzidos os Componentes Interpretáveis (CI), os quais são avaliados através do ângulo formado entre os mesmos e os Componentes Principais. O presente trabalho tem como objetivo avaliar os efeitos de diferentes estruturas de correlação via Simulação de Monte Carlo e estatística circular na distribuição dos ângulos formados entre os componentes em amostras com e sem contaminação. Foi verificado que as estruturas de correlação atuam de forma diferente nos ângulos, sendo a estrutura de Simetria Composta a que apresenta menores médias angulares para os primeiros componentes em situações de maior coeficiente de correlação. Foi verificado também que a contaminação da amostra não atua diretamente na magnitude dos valores esperados dos ângulos.
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