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On robust testing f...
On robust testing for normality in chemometrics
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Stehlik, M. (author)
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Strelec, L. (author)
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- Thulin, Måns (author)
- Uppsala universitet,Matematiska institutionen
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(creator_code:org_t)
- Elsevier BV, 2014
- 2014
- English.
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In: Chemometrics and Intelligent Laboratory Systems. - : Elsevier BV. - 0169-7439 .- 1873-3239. ; 130, s. 98-108
- Related links:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Subject headings
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- 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.
Keyword
- Trimming
- Lehmann-Bickel functional
- Model diagnostics
- Monte Carlo simulations
- Power comparison
- Robust tests for normality
Publication and Content Type
- ref (subject category)
- art (subject category)
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