Document 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, 21 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