uu.seUppsala University Publications
Change search
ReferencesLink to record
Permanent link

Direct link
On robust testing for normality in chemometrics
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics.
2014 (English)In: Chemometrics and Intelligent Laboratory Systems, ISSN 0169-7439, E-ISSN 1873-3239, Vol. 130, 98-108 p.Article in journal (Refereed) Published
Abstract [en]

The assumption that the data has been generated by a normal distribution underlies many statistical methods used in chemometrics. While such methods can be quite robust to small deviations from normality, for instance caused by a small number of outliers, common tests for normality are not and will often needlessly reject normality. It is therefore better to use tests from the little-known class of robust tests for normality. We illustrate the need for robust normality testing in chemometrics with several examples, review a class of robustified omnibus Jarque-Bera tests and propose a new class of robustified directed Lin-Mudholkar tests. The robustness and power of several tests for normality are compared in a large simulation study. The new tests are robust and have high power in comparison with both classic tests and other robust tests. A new graphical method for assessing normality is also introduced.

Place, publisher, year, edition, pages
2014. Vol. 130, 98-108 p.
Keyword [en]
Trimming, Lehmann-Bickel functional, Model diagnostics, Monte Carlo simulations, Power comparison, Robust tests for normality
National Category
Natural Sciences
URN: urn:nbn:se:uu:diva-220303DOI: 10.1016/j.chemolab.2013.10.010ISI: 000330914900014OAI: oai:DiVA.org:uu-220303DiVA: diva2:705535
Available from: 2014-03-17 Created: 2014-03-12 Last updated: 2014-03-17Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Thulin, Måns
By organisation
Department of Mathematics
In the same journal
Chemometrics and Intelligent Laboratory Systems
Natural Sciences

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 198 hits
ReferencesLink to record
Permanent link

Direct link