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On the Robustness of Type-1 and Type-2 Fuzzy Tests vs. ANOVA Tests on Means

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5755))

Abstract

This paper presents a simulation study on fuzzy tests vs. ANOVA test on means. Type-1, Interval Type-2 and ANOVA classical tests are compared through a simulated experiment for contrasting the stability of those approaches in front to a small change on sample.

We perform an experiment of comparing the means of three groups where the classical ANOVA test is very nearby to the rejection p-value and the fuzzy tests get more robust results. In this way, we use bootstrap concepts to simulate the change of a random value of the sample to view the behavior of each technique in front to these changes.

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Figueroa García, J.C., Kalenatic, D., Lopez Bello, C.A. (2009). On the Robustness of Type-1 and Type-2 Fuzzy Tests vs. ANOVA Tests on Means. In: Huang, DS., Jo, KH., Lee, HH., Kang, HJ., Bevilacqua, V. (eds) Emerging Intelligent Computing Technology and Applications. With Aspects of Artificial Intelligence. ICIC 2009. Lecture Notes in Computer Science(), vol 5755. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04020-7_19

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  • DOI: https://doi.org/10.1007/978-3-642-04020-7_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04019-1

  • Online ISBN: 978-3-642-04020-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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