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A platform for research: civil engineering, architecture and urbanism
Spatial dependence in the tails of air pollutant distributions: alternatives to the spatial correlogram
10.1002/env.934.abs
The study of the pollutants needs a better understanding of their extreme behaviours which could potentially cause adverse health effects. When analysing spatial dependence of the pollutant, the dependogram proposed by Arbia and Lafratta is preferred to the traditional correlogram used in the spatial statistics literature because it captures nonlinear relationships in the tails of the joint distributions and helps in detecting a pattern of spatial regularities. In this paper, we present a new method to estimate the spatial dependogram that uses univariate and bivariate threshold models. The method is applied to a set of hourly NO2 data collected by seven monitoring stations in the city of Rome (Italy) during the years 2000 and 2001. Copyright © 2008 John Wiley & Sons, Ltd.
Spatial dependence in the tails of air pollutant distributions: alternatives to the spatial correlogram
10.1002/env.934.abs
The study of the pollutants needs a better understanding of their extreme behaviours which could potentially cause adverse health effects. When analysing spatial dependence of the pollutant, the dependogram proposed by Arbia and Lafratta is preferred to the traditional correlogram used in the spatial statistics literature because it captures nonlinear relationships in the tails of the joint distributions and helps in detecting a pattern of spatial regularities. In this paper, we present a new method to estimate the spatial dependogram that uses univariate and bivariate threshold models. The method is applied to a set of hourly NO2 data collected by seven monitoring stations in the city of Rome (Italy) during the years 2000 and 2001. Copyright © 2008 John Wiley & Sons, Ltd.
Spatial dependence in the tails of air pollutant distributions: alternatives to the spatial correlogram
Arbia, G. (author) / Copetti, M. (author) / Lafratta, G. (author)
Environmetrics ; 20 ; 331-345
2009-05-01
15 pages
Article (Journal)
Electronic Resource
English
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