Open AccessOn the Probabilities of Environmental Extremes
Author(s) -
Benjamin Kedem,
Ryan M. Stauffer,
Xuze Zhang,
Saumyadipta Pyne
Publication year - 2021
Publication title -
international journal of statistics in medical research
Language(s) - English
Resource type - Journals
ISSN - 1929-6029
DOI - 10.6000/1929-6029.2021.10.07
Subject(s) - environmental data , computer science , task (project management) , variable (mathematics) , threshold model , statistics , algorithm , data mining , mathematics , machine learning , engineering , mathematical analysis , systems engineering , political science , law
Environmental researchers, as well as epidemiologists, often encounter the problem of determining the probability of exceeding a high threshold of a variable of interest based on observations that are much smaller than the threshold. Moreover, the data available for that task may only be of moderate size. This generic problem is addressed by repeatedly fusing the real data numerous times with synthetic computer-generated samples. The threshold probability of interest is approximated by certain subsequences created by an iterative algorithm that gives precise estimates. The method is illustrated using environmental data including monitoring data of nitrogen dioxide levels in the air.