Detecting atypical data in air pollution studies by using shorth intervals for regression
ESAIM: Probability and Statistics, Tome 9 (2005), pp. 230-240.

To validate pollution data, subject-matter experts in Airpl (an organization that maintains a network of air pollution monitoring stations in western France) daily perform visual examinations of the data and check their consistency. In this paper, we describe these visual examinations and propose a formalization for this problem. The examinations consist in comparisons of so-called shorth intervals so we build a statistical test that compares such intervals in a nonparametric regression model. This allows to detect atypical data. A practical application of the test is given.

DOI : 10.1051/ps:2005013
Classification : 62G08, 62G09, 62G10, 62P12
Mots-clés : air pollution, validation, regression, bootstrap, shorth 
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     title = {Detecting atypical data in air pollution studies by using shorth intervals for regression},
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Durot, Cécile; Thiébot, Karelle. Detecting atypical data in air pollution studies by using shorth intervals for regression. ESAIM: Probability and Statistics, Tome 9 (2005), pp. 230-240. doi : 10.1051/ps:2005013. http://www.numdam.org/articles/10.1051/ps:2005013/

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