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Multivariate and Spatial Extremes for the Analysis of Air Quality Data

机译:空气质量数据分析的多元和空间极限

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In recent years statistical analyses for monitoring the environment are increasingly in demand in different areas such as epidemiology, engineering, economy, etc. An example is the statistical monitoring of air quality, which makes it possible to statistically quantify the amount of certain pollutants in the lower troposphere. For a better understanding of the stochastic behavior of pollutants we focus on describing their extreme responses, because excessively extreme levels in the air may have implications in the environment and on human health. We then consider multivariate extreme value models and the class of maxstable processes in order to asses the frequencies of several extreme pollutant levels in central Europe and their spatial dependence structure.
机译:近年来,在诸如流行病学,工程学,经济等不同领域,对环境监测的统计分析的需求日益增长。一个例子是对空气质量的统计监测,这使得可以统计地量化大气中某些污染物的数量。对流层较低。为了更好地理解污染物的随机行为,我们着重描述污染物的极端响应,因为空气中的极端极端水平可能会对环境和人类健康产生影响。然后,我们考虑多元极值模型和最大稳定过程的类别,以便评估中欧几个极端污染物水平的频率及其空间依赖性结构。

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