Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Spatial dependence in the tails of air pollutant distributions: alternatives to the spatial correlogram
AbstractThe 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 NO2data 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
AbstractThe 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 NO2data 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
Environmetrics
Arbia, G. (Autor:in) / Copetti, M. (Autor:in) / Lafratta, G. (Autor:in)
Environmetrics ; 20 ; 331-345
01.05.2009
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
NONPARAMETRIC CORRELOGRAM TO IDENTIFY THE GEOGRAPHIC DISTANCE OF SPATIAL DEPENDENCE ON LAND PRICES
| DOAJ | 2019
| Springer Verlag | 2018
Tall Tales about Tails of Hydrological Distributions. II
| British Library Online Contents | 2000