Non-homogeneous Poisson models with a change-point: an application to ozone peaks in Mexico city

作者：Achcar Jorge Alberto; Rodrigues Eliane R^*; Paulino Carlos Daniel; Soares Paulo

来源：Environmental and Ecological Statistics, 2010, 17(4): 521-541.

DOI：10.1007/s10651-009-0114-3

• Non-homogeneous Poisson process
• Bayesian inference
• Change-point
• MCMC methods
• Air pollution data

In this paper, we use some non-homogeneous Poisson models in order to study the behavior of ozone measurements in Mexico City. We assume that the number of ozone peaks follows a non-homogeneous Poisson process. We consider four types of rate function for the Poisson process: power law, Musa-Okumoto, Goel-Okumoto, and a generalized Goel-Okumoto rate function. We also assume that a change-point may or may not be present. The analysis of the problem is performed by using a Bayesian approach via Markov chain Monte Carlo methods. The best model is chosen using the DIC criterion as well as graphical approach.

• 出版日期2010-12