Análise de componentes principais e a modelagem linear generalizada: uma associação entre o número de atendimentos hospitalares por causas respiratórias e a qualidade do ar, na Região da Grande Vitória, ES
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Data
2013-04-30
Autores
Souza, Juliana Bottoni de
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Universidade Federal do Espírito Santo
Resumo
This dissertation uses two statisticals tools, Principal Component Analisys (ACP) and Generalized Additive Model (GAM), jointly, to estimate the effect of the association between atmospheric exposure of PM10, SO2, NO2, O3 and CO and the number of admissions due respiratory diseases in children less than 6 years in the Regi˜ao da Grande Vit´oria, Brazil.Usually the atmospheric pollutants are considered the explanatory covariables in MAG, but since they have an autocorrelation structure, they must be used with caution. The PCA technique provides a new set of orthogonal variables, these variables are linear combinations of environmental variables.Therefore, We use this approach in MAG, hereafter denoted by GAM-PCA. However, the principal components obtained through the matrix of variance / covariance applied to processes indexed by time also exhibit the properties of temporal correlation. A countermeasure to attenuate the temporal correlation of the components is use the filtering method to transform the data in an atmospheric white noise process. The residual matrix is used to obtain these components and applied to the model MAG - method here called VAR-GAM-PCA. The empirical results show that this model removes the autocorrelations of the main components and indicates significant estimates of relative risk (RR) for each pollutant. The results confirm the hypotheses established, the main components have selected correlation and the autocorrelation lags. To adjust the GAM-PCA model, an ARMA(p,q) model was used in the residual matrix since that structure carried autocorrelation from the original data. The VAR model-MAG-ACP, besides producing more significant in RR estimates, generated best fit residuals. Compared to the usual modeling MAG, the two strands proposals presented better results, both in estimating the RR and the quality of the fit.
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Modelo aditivo generalizado , Modelo vetorial autoregressivo , Séries temporais
Citação
SOUZA, Juliana Bottoni de. Análise de componentes principais e a modelagem linear generalizada: uma associação entre o número de atendimentos hospitalares por causas respiratórias e a qualidade do ar, na região da Grande Vitória, ES. 2013. 66 f. Dissertação (Mestrado em Engenharia Ambiental) - Universidade Federal do Espírito Santo, Centro Tecnológico, Vitória, 2013.