Abstract

ZOZOLOTTO, H. C. Application of Stochastic Volatility Models to Air Pollution Data of Two Big Cities: Mexico City and Sao Paulo.. 2010. 105p. Dissertation (master degree) Faculty of Medicine of Ribeirao Preto, University of Sao Paulo, Ribeirao Preto, 2010. Recent studies related to environmental has been considered in all world due to increasing levels of pollution and of natural resources destruction especially, in the last years. The largest cities in the world are the ones been mostly affected by pollution and in this work we consider the analysis of air pollution data of two important cities: Mexico City and Sao Paulo. The Mexico City presents serious problems of ozone levels and Sao Paulo is the Brazilian city with the largest problems related to air pollution. Among the different models which could be used to analyze air pollution data, we consider the use of time series modeling to the weekly or daily levels of pollution. In this way, we consider the use of volatility stochastic models. This family of models has been well explored with financial data but not well explored to analyze environmental and health data. Bivariate and multivariate stochastic models under the Bayesian approach were considered to analyze the data, especially using MCMC (Markov Chain Monte Carlo) methods to obtain the posterior summary of interest, since we usually have big difficulties using standard classical inference methods.

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