Using a non-homogeneous Poisson model with spatial anisotropy and change-points to study air pollution data

A non-homogeneous Poisson process is used to study the rate at which a pollutant’s concentration exceeds a given threshold of interest. An anisotropic spatial model is imposed on the parameters of the Poisson intensity function. The main contribution here is to allow the presence of change-points in...

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Bibliographic Details
Published in:Environmental and ecological statistics 2019-06, Vol.26 (2), p.153-184
Main Authors: Rodrigues, Eliane R., Nicholls, Geoff, Tarumoto, Mario H., Tzintzun, Guadalupe
Format: Article
Language:English
Subjects:
Air pollution
Algorithms
Anisotropy
Bayesian analysis
Biomedical and Life Sciences
Chemistry and Earth Sciences
Computer Science
Computer simulation
Ecology
Health Sciences
Life Sciences
Markov analysis
Markov chains
Math. Appl. in Environmental Science
Medicine
Ozone
Parameter estimation
Parameters
Physics
Poisson density functions
Pollution data
Pollution studies
Probability theory
Statistical inference
Statistical methods
Statistics for Engineering
Statistics for Life Sciences
Theoretical Ecology/Statistics
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Summary:A non-homogeneous Poisson process is used to study the rate at which a pollutant’s concentration exceeds a given threshold of interest. An anisotropic spatial model is imposed on the parameters of the Poisson intensity function. The main contribution here is to allow the presence of change-points in time since the data may behave differently for different time frames in a given observational period. Additionally, spatial anisotropy is also imposed on the vector of change-points in order to account for the possible correlation between different sites. Estimation of the parameters of the model is performed using Bayesian inference via Markov chain Monte Carlo algorithms, in particular, Gibbs sampling and Metropolis-Hastings. The different versions of the model are applied to ozone data from the monitoring network of Mexico City, Mexico. An analysis of the results obtained is also given.
ISSN:1352-8505
1573-3009
DOI:10.1007/s10651-019-00423-6