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Application of Homogeneity Tests: Problems and Solution

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Analytical and Computational Methods in Probability Theory (ACMPT 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10684))

Abstract

The properties of the homogeneity tests of Smirnov, Lehmann-Rosenblatt, Anderson-Darling, k-sampling tests of Anderson-Darling and Zhang have been studied. Models of limiting distributions for k-sampling Anderson-Darling test under various numbers of compared samples have been presented. Power ratings have been obtained. Comparative analysis of the power of the homogeneity tests has been performed. The tests have been ordered in terms of power relative to various alternatives. Recommendations on the application of tests have been given.

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Acknowledgments

The studies were carried out with the support of the Ministry of Education and Science of the Russian Federation in the framework of the state work “Ensuring the conduct of scientific research” (No. 1.4574.2017/6.7) and the design part of the state task (No. 1.1009.2017/4.6).

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Authors and Affiliations

  1. Novosibirsk State Technical University, Novosibirsk, Russian Federation

    Boris Yu. Lemeshko, Irina V. Veretelnikova, Stanislav B. Lemeshko & Alena Yu. Novikova

Authors
  1. Boris Yu. Lemeshko
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  2. Irina V. Veretelnikova
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  3. Stanislav B. Lemeshko
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  4. Alena Yu. Novikova
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Corresponding author

Correspondence to Boris Yu. Lemeshko .

Editor information

Editors and Affiliations

  1. Department of Applied Probability and Informatics, RUDN University, Moscow, Russia

    Vladimir V. Rykov

  2. City University of Hong Kong, Hong Kong, Hong Kong

    Nozer D. Singpurwalla

  3. Steklov Mathematical Institute of Russian Academy of Sciences, Moscow, Russia

    Andrey M. Zubkov

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Lemeshko, B.Y., Veretelnikova, I.V., Lemeshko, S.B., Novikova, A.Y. (2017). Application of Homogeneity Tests: Problems and Solution. In: Rykov, V., Singpurwalla, N., Zubkov, A. (eds) Analytical and Computational Methods in Probability Theory. ACMPT 2017. Lecture Notes in Computer Science(), vol 10684. Springer, Cham. https://doi.org/10.1007/978-3-319-71504-9_38

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  • DOI: https://doi.org/10.1007/978-3-319-71504-9_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-71503-2

  • Online ISBN: 978-3-319-71504-9

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