Detecting atypical data in air pollution studies by using shorth intervals for regression
Université Paris Sud, Bâtiment 425, 91405 Orsay Cedex, France;
2 ; Air Pays de la Loire, 2 rue A. Kastler, BP 30723, 44307 Nantes Cedex 3, France.
Revised: 8 April 2005
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