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Resistant outlier rules and the non-Gaussian case

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  • Carling, Kenneth

    ()
    (IFAU - Office of Labour Market Policy Evaluation)

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    Abstract

    The techniques of exploratory data analysis include a resistant rule, based on a linear combination of quartiles, for identification of outliers. This paper shows that the substitution of the quartiles with the median leads to a better performance in the non-Gaussian case. The improvement occurs in terms of resistance and efficiency, and an outside rate that is less affected by the sample size. The paper also studies issues of practical importance in the spirit of robustness by considering moderately skewed and fat tail distributions obtatined as special cases of the Generalized Lambda Distribution.

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    File URL: http://www.ifau.se/Upload/pdf/se/2001/wp01-07.pdf
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    Bibliographic Info

    Paper provided by IFAU - Institute for Evaluation of Labour Market and Education Policy in its series Working Paper Series with number 2001:7.

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    Length: 14 pages
    Date of creation: 01 Sep 1998
    Date of revision:
    Publication status: Published in Computational Statistics and Data Analysis, 2000, pages 249-258.
    Handle: RePEc:hhs:ifauwp:2001_007

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    Related research

    Keywords: Asymptotic efficiency; Generalized Lambda Distribution; Kurtosis; Outside rate; Resistance; Skewness; Small-sample bias;

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