Environmental and Ecological Statistics

, Volume 18, Issue 2, pp 271-290

First online:

Using stochastic volatility models to analyse weekly ozone averages in Mexico City

  • Jorge A. AchcarAffiliated withFaculdade de Medicina, Ribeirão Preto, Universidade de São Paulo
  • , Eliane R. RodriguesAffiliated withInstituto de Matemáticas, UNAM Email author 
  • , Guadalupe TzintzunAffiliated withInstituto Nacional de Ecología, Secretaría de Medio Ambiente y Recursos Naturales

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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.


Stochastic volatility models Ozone air pollution Times series Bayesian inference MCMC methods