1.Faculdade de Medicina, Ribeir?o Preto,Universidade de S?o Paulo,S?o Paulo,Brazil;2.Instituto de Matemáticas, UNAM,Mexico,Mexico;3.Instituto Nacional de Ecología,Secretaría de Medio Ambiente y Recursos Naturales,Mexico,Mexico
Abstract:
In this paper we make use of some stochastic volatility models to analyse the behaviour of a weekly ozone average measurements
series. The models considered here have been used previously in problems related to financial time series. Two models are
considered and their parameters are estimated using a Bayesian approach based on Markov chain Monte Carlo (MCMC) methods.
Both models are applied to the data provided by the monitoring network of the Metropolitan Area of Mexico City. The selection
of the best model for that specific data set is performed using the Deviance Information Criterion and the Conditional Predictive
Ordinate method.