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A Simulation Study Goodness-of-Fit Tests for the Skewed Normal Distribution

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Chaos, Complexity and Leadership 2012

Part of the book series: Springer Proceedings in Complexity ((SPCOM))

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Abstract

This research is based on the insufficiency of the normal distribution known as EDF goodness-of fit tests(Kolmogorov-Smirnov (K-S), Anderson-Darling (A-D) and Cramer-von Mises (W)). Thus by adding another component which has been proven to be viable (Liao-Shimokawa (Ln)) a Monte-Carlo simulation technique have been made to make comparison. In simulation, α = 5 β = 1 as gamma distribution μ = 0 σ = 1 Extreme-Value, α = 2 β = 1 Weibull ve degrees of freedom χ 2 distributions have been used.

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Author information

Authors and Affiliations

  1. Turkish Statistical Institute, Ankara, Turkey

    Emre E. Sarısoy

  2. Faculty of Economics and Administrative Science, Health Institution Management Department, Gazi University, Ankara, Turkey

    Nihan Potas

  3. Department of Statistics, Ankara University, Ankara, Turkey

    Mahmut Kara

Authors
  1. Emre E. Sarısoy
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  2. Nihan Potas
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  3. Mahmut Kara
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Corresponding author

Correspondence to Emre E. Sarısoy .

Editor information

Editors and Affiliations

  1. International Science Association, Ankara, Turkey

    Santo Banerjee

  2. International Science Association, Ankara, Turkey

    Şefika Şule Erçetin

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Sarısoy, E.E., Potas, N., Kara, M. (2014). A Simulation Study Goodness-of-Fit Tests for the Skewed Normal Distribution. In: Banerjee, S., Erçetin, Ş. (eds) Chaos, Complexity and Leadership 2012. Springer Proceedings in Complexity. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7362-2_36

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  • DOI: https://doi.org/10.1007/978-94-007-7362-2_36

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-7361-5

  • Online ISBN: 978-94-007-7362-2

  • eBook Packages: Physics and AstronomyPhysics and Astronomy (R0)

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