Research Article

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

Durot, Cécile^a1 and Thiébot, Karelle^a1a2

^a1 Université Paris Sud, Bâtiment 425, 91405 Orsay Cedex, France; cecile.durot@math.u-psud.fr

^a2 ; Air Pays de la Loire, 2 rue A. Kastler, BP 30723, 44307 Nantes Cedex 3, France.

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.

(Received December 15 2003)

(Revised April 8 2005)

(Online publication November 15 2005)

Key Words:

• Air pollution;
• validation;
• regression;
• bootstrap;
• shorth.

Mathematics Subject Classification:

• 62G08;
• 62G09;
• 62G10;
• 62P12