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

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

Received: 15 December 2003
Revised: 8 April 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.