Detection of outlying observations using the Akaike information criterion

• Autorzy: Andrzej Kornacki
• Języki publikacji: EN

Abstrakty

EN

For the detection of outliers (observations which are seemingly different from the others) the method of testing hypotheses is most often used. This approach, however, depends on the level of significance adopted by the investigator. Moreover, it can lead to the undesirable effect of “masking” of the outliers. This paper presents an alternative method of outlier detection based on the Akaike information criterion. The theory presented is applied to analysis of the results of beet leaf mass determination.

Słowa kluczowe

EN

outliers; entropy; Akaike information criterion; Dixon test; Grubbs test

• Wydawca: De Gruyter Open
• Czasopismo: Biometrical Letters
• Rocznik: 2013
• Tom: 50
• Numer: 2
• Strony: 117-126

Daty

wydano

2013-12-01

online

2013-12-10

Twórcy

autor

Andrzej Kornacki

• Department of Applied Mathematics and Computer Science, University of Life Sciences in Lublin, Akademicka 13, 20-950 Lublin, Poland

Bibliografia

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Identyfikatory

DOI

10.2478/bile-2013-0022