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Issue ESAIM: PS
Volume 9, 2005
Page(s) 230 - 240
DOI 10.1051/ps:2005013

ESAIM: P&S, June 2005, Vol. 9, pp. 230-240
DOI: 10.1051/ps:2005013

Detecting atypical data in air pollution studies by using shorth intervals for regression

Cécile Durot1 and Karelle Thiébot1, 2

1  Université Paris Sud, Bâtiment 425, 91405 Orsay Cedex, France; cecile.durot@math.u-psud.fr
2  Supported by Air Pays De La Loire; Air Pays de la Loire, 2 rue A. Kastler, BP 30723, 44307 Nantes Cedex 3, France.


(Received December 15, 2003. Revised April 8, 2005.)

Abstract
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.


Mathematics Subject Classification. 62G08, 62G09, 62G10, 62P12.

Key words: Air pollution, validation, regression, bootstrap, shorth.


© EDP Sciences, SMAI 2005


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