Detecting atypical data in air pollution studies by using shorth intervals for regression
ESAIM: Probability and Statistics, Volume 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
Keywords: air pollution, validation, regression, bootstrap, shorth
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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, Volume 9 (2005), pp. 230-240. doi : 10.1051/ps:2005013. http://www.numdam.org/articles/10.1051/ps:2005013/

[1] L. Bel, L. Bellanger, V. Bonneau, G. Ciuperca, D. Dacunha-Castelle, C. Deniau, B. Ghattas, Y. Misiti and G. Oppenheim, Éléments de comparaison de prévisions statistiques des pics d'ozone. Rev. Statist. App. 3 (1999) 7-25. | Numdam

[2] C. Durot and K. Thiébot. Bootstrapping the shorth for regression. Submitted (2003). | Numdam

[3] P. Hall, J.W. Kay and D.M. Titterington, Asymptotically optimal difference-based estimation of variance in nonparametric regression. Biometrika 77 (1990) 521-529.

[4] K. Thiébot, Synthèse de l'enquête sur la procédure de validation de données dans les résaux de surveillance de pollution athmosphérique. Technical report, Air Pays de la Loire (1998).

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