In this paper, we consider some non-homogeneous Poisson models to estimate the probability that an air quality standard is exceeded a given number of times in a time interval of interest. We assume that the number of exceedances occurs according to a non-homogeneous Poisson process (NHPP). This Pois
Estimating the number of ozone peaks in Mexico City using a non-homogeneous Poisson model
✍ Scribed by Jorge A. Achcar; Adrián A. Fernández-Bremauntz; Eliane R. Rodrigues; Guadalupe Tzintzun
- Publisher
- John Wiley and Sons
- Year
- 2008
- Tongue
- English
- Weight
- 273 KB
- Volume
- 19
- Category
- Article
- ISSN
- 1180-4009
- DOI
- 10.1002/env.890
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✦ Synopsis
Abstract
In this paper, we consider the problem of estimating the number of times an air quality standard is exceeded in a given period of time. A non‐homogeneous Poisson model is proposed to analyse this issue. The rate at which the Poisson events occur is given by a rate function λ(t), t ≥ 0. This rate function also depends on some parameters that need to be estimated. Two forms of λ(t), t ≥ 0 are considered. One of them is of the Weibull form and the other is of the exponentiated‐Weibull form. The parameters estimation is made using a Bayesian formulation based on the Gibbs sampling algorithm. The assignation of the prior distributions for the parameters is made in two stages. In the first stage, non‐informative prior distributions are considered. Using the information provided by the first stage, more informative prior distributions are used in the second one. The theoretical development is applied to data provided by the monitoring network of Mexico City. The rate function that best fit the data varies according to the region of the city and/or threshold that is considered. In some cases the best fit is the Weibull form and in other cases the best option is the exponentiated‐Weibull. Copyright © 2007 John Wiley & Sons, Ltd.
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