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On the Kuiper test for normality with mean and variance unknown

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  • R. Srinivasan

Abstract

Summary A modified form of the Kuiper statistic Vn is developed for testing the composite hypothesis that a sample of size n comes from a normal population with unspecified mean and variance. Its distribution is derived using Monte Carlo methods. Power comparison with the adjusted Kuiper test proposed by Louter and Koerts [6] indicates that our test is superior with respect to certain alternatives.

Suggested Citation

  • R. Srinivasan, 1971. "On the Kuiper test for normality with mean and variance unknown," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 25(3), pages 153-157, September.
    • Handle: RePEc:bla:stanee:v:25:y:1971:i:3:p:153-157
    DOI: 10.1111/j.1467-9574.1971.tb00143.x
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    Cited by:

    1. Bielak, Łukasz & Grzesiek, Aleksandra & Janczura, Joanna & Wyłomańska, Agnieszka, 2021. "Market risk factors analysis for an international mining company. Multi-dimensional, heavy-tailed-based modelling," Resources Policy, Elsevier, vol. 74(C).
    2. Marcin Pitera & Aleksei Chechkin & Agnieszka Wyłomańska, 2022. "Goodness-of-fit test for $$\alpha$$ α -stable distribution based on the quantile conditional variance statistics," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(2), pages 387-424, June.
    3. Agnieszka Wyłomańska & D Robert Iskander & Krzysztof Burnecki, 2020. "Omnibus test for normality based on the Edgeworth expansion," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-36, June.

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