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

Cécile Durot; Karelle Thiébot

ESAIM: Probability and Statistics (2010)

  • Volume: 9, page 230-240
  • ISSN: 1292-8100

Abstract

top
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.

How to cite

top

Durot, Cécile, and Thiébot, Karelle. "Detecting atypical data in air pollution studies by using shorth intervals for regression." ESAIM: Probability and Statistics 9 (2010): 230-240. <http://eudml.org/doc/104334>.

@article{Durot2010,
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. },
author = {Durot, Cécile, Thiébot, Karelle},
journal = {ESAIM: Probability and Statistics},
keywords = {Air pollution; validation; regression; bootstrap; shorth.; regression; shorth},
language = {eng},
month = {3},
pages = {230-240},
publisher = {EDP Sciences},
title = {Detecting atypical data in air pollution studies by using shorth intervals for regression},
url = {http://eudml.org/doc/104334},
volume = {9},
year = {2010},
}

TY - JOUR
AU - Durot, Cécile
AU - Thiébot, Karelle
TI - Detecting atypical data in air pollution studies by using shorth intervals for regression
JO - ESAIM: Probability and Statistics
DA - 2010/3//
PB - EDP Sciences
VL - 9
SP - 230
EP - 240
AB - 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.
LA - eng
KW - Air pollution; validation; regression; bootstrap; shorth.; regression; shorth
UR - http://eudml.org/doc/104334
ER -

References

top
  1. L. Bel, L. Bellanger, V. Bonneau, G. Ciuperca, D. Dacunha-Castelle, C. Deniau, B. Ghattas, Y. Misiti and G. Oppenheim, Éléments de comparaison de prévisions statistiques des pics d'ozone. Rev. Statist. App.3 (1999) 7–25.  
  2. C. Durot and K. Thiébot. Bootstrapping the shorth for regression. Submitted (2003).  Zbl1187.62034
  3. P. Hall, J.W. Kay and D.M. Titterington, Asymptotically optimal difference-based estimation of variance in nonparametric regression. Biometrika77 (1990) 521–529.  
  4. K. Thiébot, Synthèse de l'enquête sur la procédure de validation de données dans les résaux de surveillance de pollution athmosphérique. Technical report, Air Pays de la Loire (1998).  

NotesEmbed ?

top

You must be logged in to post comments.

To embed these notes on your page include the following JavaScript code on your page where you want the notes to appear.

Only the controls for the widget will be shown in your chosen language. Notes will be shown in their authored language.

Tells the widget how many notes to show per page. You can cycle through additional notes using the next and previous controls.

    
                

Note: Best practice suggests putting the JavaScript code just before the closing </body> tag.