Environmental and Ecological Statistics

, Volume 18, Issue 2, pp 271–290

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

  • Jorge A. Achcar
  • Eliane R. Rodrigues
  • Guadalupe Tzintzun
Article

DOI: 10.1007/s10651-010-0132-1

Cite this article as:
Achcar, J.A., Rodrigues, E.R. & Tzintzun, G. Environ Ecol Stat (2011) 18: 271. doi:10.1007/s10651-010-0132-1

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.

Keywords

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

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Jorge A. Achcar
    • 1
  • Eliane R. Rodrigues
    • 2
  • Guadalupe Tzintzun
    • 3
  1. 1.Faculdade de Medicina, Ribeirão PretoUniversidade de São PauloSão PauloBrazil
  2. 2.Instituto de Matemáticas, UNAMMexicoMexico
  3. 3.Instituto Nacional de EcologíaSecretaría de Medio Ambiente y Recursos NaturalesMexicoMexico

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