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Resistant outlier rules and the non-Gaussian case

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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.

Suggested Citation

  • Carling, Kenneth, 1998. "Resistant outlier rules and the non-Gaussian case," Working Paper Series 2001:7, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    • Handle: RePEc:hhs:ifauwp:2001_007
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    References listed on IDEAS

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    1. A.C. Kimber, 1990. "Exploratory Data Analysis for Possibly Censored Data from Skewed Distributions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 39(1), pages 21-30, March.
    2. Vic Barnett, 1978. "The Study of Outliers: Purpose and Model," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 27(3), pages 242-250, November.
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    More about this item

    Keywords

    Asymptotic efficiency; Generalized Lambda Distribution; Kurtosis; Outside rate; Resistance; Skewness; Small-sample bias;
    All these keywords.

    JEL classification:

    • C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other

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